Một số mô hình đo lường rủi ro trên thị trường chứng khoán Việt Nam

Header Page of 89 Bộ GIáO DụC Và ĐàO TạO TRƯờNG ĐạI HọC KINH Tế QUốC DÂN * hoàng đức mạnh MT S Mễ HèNH O LNG RI RO TRấN TH TRNG CHNG KHON VIT NAM Chuyờn ngnh : Kinh t hc (iu khin hc Kinh t) Mã số : 62 31 01 01 LUậN áN TIN S KINH tế Ngời hớng dẫn khoa học: ts trần trọng nguyên ts nguyễn mạnh Hà NộI - 2014 Footer Page of 89 Header Page of 89 LI CAM OAN Tụi xin cam oan õy l cụng trỡnh nghiờn cu khoa hc c lp ca tụi Cỏc thụng tin, d liu, s liu lun ỏn u cú ngun gc rừ rng, c th Kt qu nghiờn cu lun ỏn l trung thc v cha tng c cụng b bt k cụng trỡnh nghiờn cu no khỏc Nghiờn cu sinh Hong c Mnh Footer Page of 89 Header Page of 89 LI CM N Trong quỏ trỡnh thc hin lun ỏn, tụi ó nhn c s giỳp nhit tỡnh v to iu kin thun li ca giỏo viờn hng dn, ng nghip, gia ỡnh v bn bố Xin chõn thnh cm n TS.Trn Trng Nguyờn v TS.Nguyn Mnh Th v s hng dn nhit tỡnh sut quỏ trỡnh lm lun ỏn Xin gi li cm n ti cỏc thy giỏo, cụ giỏo Khoa Toỏn Kinh tTrng i hc Kinh t Quc dõn ó giỳp v cú nhng gúp ý lun ỏn c hon thnh tt hn Xin gi li cm n ti cỏc cỏn b thuc Vin o to Sau i hc- Trng i hc Kinh t Quc dõn ó to iu kin v cỏc th tc hnh chớnh, v hng dn quy trỡnh thc hin ton b quỏ trỡnh hc Xin cỏm n b m v gia ỡnh ó ng viờn, giỳp sut thi gian qua Footer Page of 89 Header Page of 89 i MC LC LI CAM OAN LI CM N DANH MC CH VIT TT DANH MC BNG V HèNH M U CHNG 1: TNG QUAN V O LNG RI RO V THC TRNG O LNG RI RO TRấN TH TRNG CHNG KHON VIT NAM 1.1 Ri ro v o lng ri ro 1.1.1 Khỏi nim v phõn loi ri ro 1.1.2 o lng ri ro 1.2 Tng quan v mụ hỡnh o lng ri ro 10 1.3 Mt s mụ hỡnh o lng ri ro 25 1.3.1 Mụ hỡnh o lng bin ng 25 1.3.2 Mụ hỡnh CAPM 27 1.3.3 Mụ hỡnh VaR 28 1.3.4 Mụ hỡnh ES 28 1.3.5 Cỏc phng phỏp c lng mụ hỡnh VaR v ES 30 1.3.6 Hu kim mụ hỡnh VaR v ES 50 1.4 Thc trng o lng ri ro trờn th trng chng khoỏn Vit Nam 53 1.4.1 Quỏ trỡnh hỡnh thnh v phỏt trin ca th trng chng khoỏn Vit Nam 53 1.4.2 o lng ri ro trờn th trng chng khoỏn Vit Nam 62 1.5 Kt lun chng 66 CHNG 2: Mễ HèNH O LNG S PH THUC CA CC CHUI LI SUT CHNG KHON 68 2.1 o lng s ph thuc ca cỏc chui li sut chng khoỏn 68 2.1.1 Cỏc giỏ tr ng vt ngng ca cỏc chui li sut chng khoỏn 69 2.1.2 Mụ hỡnh GARCH-copula ng 70 Footer Page of 89 Header Page of 89 ii 2.2 Kt qu phõn tớch thc nghim 73 2.2.1 Mụ t s liu 73 2.2.2 Phõn tớch c im bin ng cựng chiu ca cỏc cp c phiu v ch s th trng 78 2.2.3 o lng s ph thuc ca cỏc chui li sut bng phng phỏp copula 85 2.3 Kt lun chng 97 CHNG 3: Mễ HèNH O LNG RI RO CA DANH MC U T TRấN TH TRNG CHNG KHON VIT NAM 99 3.1 Mụ hỡnh o bin ng ca li sut chng khoỏn 99 3.1.1 Mụ hỡnh GARCH n bin 100 3.1.2 Mụ hỡnh GARCH a bin 101 3.2 Phõn tớch ri ro h thng ca mt s c phiu 105 3.3 Mụ hỡnh VaR v ES 110 3.3.1 c lng VaR v ES cho chui li sut ti sn 110 3.3.2 c lng VaR ca danh mc u t nhiu ti sn 118 3.3.3 c lng ES ca danh mc u t nhiu ti sn 129 3.4 Kt lun chng 132 MT S KHUYN NGH V O LNG RI RO TRấN TH TRNG CHNG KHON VIT NAM 135 KT LUN V XUT HNG NGHIấN CU TIP THEO 139 DANH MC CC CễNG TRèNH NGHIấN CU CA TC GI 141 DANH MC TI LIU THAM KHO 142 PH LC 160 Footer Page of 89 Header Page of 89 iii DANH MC CC T VIT TT APT : Arbitrage Pricing Theory/ Lý thuyt nh giỏ c li ARMA : Autoregressive Moving Average Process/ Quỏ trỡnh trung bỡnh trt t hi quy BEKK : Baba, Engle, Kraft and Kroner BVH : Tp on Bo Vit CAPM : Capital Asset Pricing Model/ Mụ hỡnh nh giỏ ti sn CCC : Constant Conditional Correlation/ Tng quan iu kin hng CII : CTCP u t H tng K thut TP.HCM CSM : CTCP Cụng nghip Cao su Min Nam CTCP : Cụng ty C phn CTG : Ngõn hng Thng mi C phn Cụng Thng Vit Nam CVaR : Conditional Value at Risk/ Giỏ tr ri ro cú iu kin DCC : Dynamic Conditional Correlation/ Tng quan iu kin ng DIG : Tng Cụng ty C phn u t Phỏt trin Xõy dng DPM : Tng Cụng ty Phõn bún v Húa cht Du khớ CTCP DRC : Cụng ty C phn Cao su Nng DN : Doanh nghip EIB : Ngõn hng Thng mi C phn Xut Nhp khu Vit Nam ES : Expected Shortfall/ Tn tht k vng EVT : Extreme Value Theory/ Lý thuyt giỏ tr cc tr FPT : Cụng ty C phn FPT GARCH : Generalized Autoregressive Conditional Heteroscedasticity Models/ Mụ hỡnh phng sai cú iu kin ca sai s thay i t hi quy tng quỏt Footer Page of 89 Header Page of 89 iv GMD : CTCP i lý Liờn hip Vn chuyn GPD : Generalized Pareto Distribution/ Phõn phi Pareto tng quỏt GO-GARCH: Generalized Orthogonal- GARCH/ Mụ hỡnh GARCH trc giao tng quỏt HAG : Cụng Ty C Phn Hong Anh Gia Lai HPG : Cụng ty C phn Tp on Hũa Phỏt HSG : Cụng ty C phn Tp on Hoa Sen IJC : Cụng ty c phn Phỏt trin H tng K thut KDC : CTCP Kinh ụ MB : Maximum Block/ Cc i MBB : Ngõn hng Thng mi C phn Quõn i KMV : Kealhofer Merton Vasicek MGARCH : Multivariate GARCH / GARCH a bin MSN : Cụng ty C phn Tp on Ma San MV : MeanVariance/ Trung bỡnh-Phng sai NT : Nh u t OGC : CTCP Tp on i Dng O-GARCH : Orthogonal- GARCH/ GARCH trc giao PGD : CTCP Phõn phi Khớ thp p Du khớ Vit Nam PNJ : CTCP Vng bc ỏ quý Phỳ Nhun POT : Peaks Over Threshold/ Cỏc nh vt ngng PVD : Tng CTCP Khoan v Dch v Khoan Du khớ PVF : Tng Cụng ty Ti chớnh C phn Du khớ Vit Nam REE : Cụng ty C phn C in lnh Footer Page of 89 Header Page of 89 v SBT : Cụng ty C phn Bourbon Tõy Ninh SIM : Single Index Model/ Mụ hỡnh ch s n SSI : CTCP Chng khoỏn Si Gũn STB : Ngõn hng Thng mi C phn Si Gũn Thng Tớn TTCK : Th trng chng khoỏn UBCKNN : y ban chng khoỏn nh nc VCB : Ngõn hng TMCP Ngoi Thng Vit Nam VIC : Tp on VINGROUP CTCP VNM : Cụng ty C phn Sa Vit Nam VSH : CTCP Thy in Vnh Sn Sụng Hinh VaR : Value at Risk/ Giỏ tr ri ro Footer Page of 89 Header Page of 89 vi DANH MC BNG, HèNH V BNG Bng 1.1 H s ph thuc uụi 45 Bng 2.1 Thng kờ mụ t cỏc chui li sut .74 Bng 2.2 Phõn tớch tng quan 77 Bng 2.3 S lng cỏc giỏ tr ng vt ngng ca cỏc hm ng vt ngng giai on t 1/2/2008 n 27/2/2009 80 Bng 2.4 S lng cỏc giỏ tr ng vt ngng ca cỏc hm ng vt ngng ngoi giai on t 1/2/2008 n 27/2/2009 80 Bng 2.5 c lng cỏc tham s copula khụng iu kin ca cỏc chui li sut vi RVNINDEX 86 Bng 2.6 Kim nh tớnh dng 88 Bng 2.7 Thng kờ mụ t cỏc chui h s tng quan mụ hỡnh GARCH-copula-TDCC 90 Bng 2.8 Kt qu hi quy h s tng quan ca cỏc cp theo BG .90 Bng 2.9 Thng kờ mụ t cỏc chui h s Kendall .91 Bng 2.10 Thng kờ mụ t ca cỏc chui h s ph thuc uụi di .94 Bng 2.11 Thng kờ mụ t ca cỏc chui h s ph thuc uụi trờn 94 Bng 2.12 Kt qu hi quy h s ph thuc uụi di ca cỏc cp theo BG .95 Bng 2.13 Kt qu hi quy h s ph thuc uụi trờn ca cỏc cp theo BG 95 Bng 3.1 So sỏnh kt qu c lng ca mụ hỡnh GARCH v CCC .103 Bng 3.2 Giỏ tr hip phng sai ca cỏc cp li sut 108 Bng 3.3 Bng giỏ tr thng kờ mụ t cỏc h s beta 109 Bng 3.4 Giỏ tr VaR v ES ca mi c phiu bng phng phỏp EVT 117 Bng 3.5 Kt qu c lng VaR ca 1241 quan sỏt u tiờn mc 0.95 v 0.99 .125 Bng 3.6 Kt qu hu kim cỏc mụ hỡnh c lng VaR 127 Bng 3.7 c lng ES ca 1241 quan sỏt u tiờn mc 0.95 v 0.99 129 Bng 3.8 Hu kim ES mc 0.95 v 0.99 130 Footer Page of 89 Header Page 10 of 89 vii HèNH V Hỡnh 1.1 Minh cho phng phỏp BM v phng phỏp POT .15 Hỡnh 1.2 th phõn tỏn ca chui li sut RHNX v RVNINDEX 17 Hỡnh 1.3 th chui li sut ch s VNINDEX 26 Hỡnh 1.4 Giỏ tr VaR v ES ca li sut ti sn 29 Hỡnh 1.5 Giỏ tr VaR ca phõn phi chun v phõn phi uụi dy 29 Hỡnh 1.6 Miờu t hm ỏnh x danh mc tuyn tớnh 35 Hỡnh 1.7 Miờu t hm ỏnh x danh mc khụng tuyn tớnh .35 Hỡnh 1.8 D-vine 49 Hỡnh 1.9 C-Vine 49 Hỡnh 1.10 Minh hu kim VaR 51 Hỡnh 1.11 th VNINDEX giai on 2000-2005 54 Hỡnh 1.12 th VNINDEX giai on 2006-2007 56 Hỡnh 1.13 th VNINDEX giai on 2008-2012 57 Hỡnh 2.1 th cỏc chui li sut 77 Hỡnh 2.2 th cỏc hm ng vt ngng 78 Hỡnh 2.3 Din bin lói sut c bn 79 Hỡnh 2.4 th chui h s tng quan mụ hỡnh GARCH-copula-T-DCC 89 Hỡnh 2.5 th s bin ng ca h s Kendall mụ hỡnh GARCH-Clayton ng 91 Hỡnh 2.6 th s thay i h s ph thuc uụi trờn v h s ph thuc uụi di ca cỏc cp li sut mụ hỡnh GARCH-copula-SJC ng 93 Hỡnh 2.7 th thay i mc ph thuc ca cỏc cp bng h s tng quan v cỏc h s ph thuc uụi .97 Hỡnh 3.1 th cỏc chui hip phng sai 104 Hỡnh 3.2 th cỏc chui beta cú iu kin 108 Hỡnh 3.3 th Q-Q ca chui REIB 110 Hỡnh 3.4 th hm trung bỡnh vt ngng mu ca chui REIB 111 Hỡnh 3.5 th Hill ca chui REIB 112 Hỡnh 3.6 th khong tin cy VaR(0.95) v ES(0.95) ca REIB vi tin cy 95% 116 Hỡnh 3.7 Hu kim mụ hỡnh VaR(0.99) .128 Hỡnh 3.8 Hu kim mụ hỡnh ES(0.99) 132 Footer Page 10 of 89 Header Page 179 of 89 RKDC RITA RHNX RVNINDEX Footer Page 179 of 89 169 Header Page 180 of 89 RBVH RCTG RDIG Footer Page 180 of 89 170 Header Page 181 of 89 RDPM REIB RHPG Footer Page 181 of 89 171 Header Page 182 of 89 RHSG RIJC RMBB RMSN Footer Page 182 of 89 172 Header Page 183 of 89 ROGC RPVF RSBT RVCB Footer Page 183 of 89 173 Header Page 184 of 89 174 Ph lc Kt qu c lng hỡnh GARCH-copula ng ca cỏc chui li sut vi RVNINDEX Copula H s DF RCII RFPT RGMD RKDC RITA RHNX 13.6102 13.4555 18.9732 11.6544 12.7924 16.3427 ALPHA 0.05 0.047 0.0768 0.0355 0.065 0.0383 BETA 0.95 0.943 0.875 0.9645 0.9142 0.9554 Akaike -730.65 -925.668 -936.922 -535.775 -799.275 -1751.88 BIC -714.73 -909.746 -921 -519.853 -783.354 -1735.96 0.028 0.044 0.0723 0.0306 0.023 0.0408 0.9681 0.9412 0.8551 0.9584 0.9569 0.9513 -698.75 -903.451 -928.149 -530.647 -756.309 -1744.4 -688.13 -892.836 -917.535 -520.033 -745.695 -1733.78 OMEGA 0.1275 0.0935 0.1559 0.1122 0.0977 0.0387 Clayton-vary ALPHA1 -0.7456 -0.5436 -0.842 -0.6755 -0.6986 -0.2008 ALPHA2 0.9188 0.9614 0.8872 0.9542 0.2511 0.9868 -547.72 -687.67 -706.635 -429.387 -532.967 -1365.04 -531.8 -671.749 -690.713 -413.466 -517.046 -1349.12 OMEGA-UP 0.098 2.6387 3.3066 1.2695 2.5394 8.9312 ALPHA1-UP -0.4506 -10 -9.9594 -4.2606 -8.0196 1.356 ALPHA2-UP 0.9717 -0.1882 -0.9201 -0.9996 -0.0878 5.6847 OMEGA-LOW 1.3117 2.0463 2.3378 0.9326 0.1154 2.7446 ALPHA1-LOW -6.7198 -10 -9.9945 -5.5001 -0.6594 -0.0373 ALPHA2-LOW 0.5239 0.334 -0.0442 0.8464 0.9383 -3.1622 Akaike -686.4 -819.354 -863.186 -492.337 -750.085 -1309.99 -654.56 -787.511 -831.343 -460.494 -718.241 -1278.15 T-DCC ALPHA BETA Gauss-DCC Akaike BIC Akaike BIC SJC-vary BIC Footer Page 184 of 89 Header Page 185 of 89 175 Ph lc Kt qu c lng mụ hỡnh GARCH Variable RBVH RCTG RDIG Coefficient Prob Variable CoefficientProb Variable CoefficientProb C -0.00025 0.8031C -0.00141 0.0246C AR(1) 0.142602 0.0000AR(3) -0.5725 0.0000AR(1) MA(3) Variance Equation C 0.154938 0.0007 0.531944 0.0000 Variance Equation 0.000151 0.0041C -0.0025 0.0151 Variance Equation 4.00E-05 0.0000C 0.000225 0.0000 RESID(-1)^2 0.222133 0.0007RESID(-1)^2 0.226619 0.0000RESID(-1)^2 0.461653 0.0000 GARCH(-1) 0.601012 0.0000GARCH(-1) 0.733516 0.0000GARCH(-1) 0.433396 0.0000 Variable RDPM REIB RHPG Coefficient Prob Variable Coefficient Prob Variable Coefficient Prob C -0.00063 0.3334 C AR(1) 0.085453 0.0036 Variance Equation C -0.00057 0.3663 C AR(1) Variance Equation 5.40E-05 0.0000 C -0.00216 0.0325 0.125774 0.0001 Variance Equation 0.000115 0.0000 C 0.000725 0.0000 RESID(-1)^2 0.212044 0.0000 RESID(-1)^2 0.240006 0.0000 RESID(-1)^2 0.177117 0.0000 GARCH(-1) Variable 0.702183 0.0000 GARCH(-1) RHSG RIJC RMBB Coefficient Prob Variable Coefficient Prob Variable Coefficient Prob C -0.00116 0.3807 C AR(1) 0.215811 0.0000 AR(1) AR(4) 0.085371 0.0058 Variance Equation C 0.44471 0.0000 -0.00275 0.0191 C 0.09949 0.0439 Variance Equation 0.000109 0.0672 C -0.00108 0.2284 Variance Equation 0.000136 0.0066 C 3.70E-05 0.0213 RESID(-1)^2 0.104982 0.0089 RESID(-1)^2 0.355621 0.0000 RESID(-1)^2 0.223905 0.0048 GARCH(-1) Footer Page 185 of 89 0.772676 0.0000 GARCH(-1) 0.59809 0.0000 GARCH(-1) 0.711445 0.0000 Header Page 186 of 89 Variable 176 RMSN ROGC RPVF Coefficient Prob Variable Coefficient Prob Variable Coefficient Prob C 0.000885 0.3483 C -0.00205 0.117 C -0.00111 0.3176 AR(1) 0.174102 0.0000 AR(1) 0.125966 0.0016 AR(1) 0.156312 0.0000 AR(7) 0.070918 0.0242 Variance Equation C Variance Equation 6.35E-05 0.0027 C Variance Equation 5.71E-05 0.1968 C 6.55E-05 0.0917 RESID(-1)^2 0.164602 0.0002 RESID(-1)^2 0.105937 0.0441 RESID(-1)^2 0.118272 0.0068 GARCH(-1) Variable 0.726453 0.0000 GARCH(-1) 0.834101 0.0000 GARCH(-1) 0.812692 0.0000 RSBT RVCB RCII Coefficient Prob Variable Coefficient Prob Variable Coefficient Prob C -0.00036 0.6801 C -0.00145 0.0159 C -0.00074 0.284 AR(1) 0.153983 0.0000 AR(1) 0.033536 0.3723 AR(1) 0.141344 0.0000 AR(4) 0.052831 0.0714 MA(3) Variance Equation C -0.1169 0.0011 Variance Equation 6.85E-05 0.0006 C Variance Equation 0.000154 0.0000 C 3.09E-05 0.0002 RESID(-1)^2 0.14586 0.0000 RESID(-1)^2 0.299202 0.0000 RESID(-1)^2 0.227538 0.0000 GARCH(-1) 0.76254 0.0000 GARCH(-1) Variable C AR(1) RGMD RKDC Coefficient Prob Variable Coefficient Prob Variable Coefficient Prob -0.0002 0.8004 C 0.065206 0.0000 AR(1) Footer Page 186 of 89 -0.00214 0.0033 C -0.00141 0.0355 0.185913 0.0000 AR(1) 0.163562 0.0000 Variance Equation 0.000126 0.0000 C RESID(-1)^2 0.334762 0.0000 RESID(-1)^2 GARCH(-1) 0.758045 0.0000 RFPT Variance Equation C 0.396695 0.0000 GARCH(-1) 0.603916 0.0000 GARCH(-1) Variance Equation 4.49E-05 0.0000 0.24789 0.0000 RESID(-1)^2 0.014368 0.0000 0.715999 0.0000 GARCH(-1) 0.985632 0.0000 Header Page 187 of 89 Variable 177 RITA RHNX RVNINDEX Coefficient Prob Variable Coefficient Prob Variable Coefficient Prob C -0.00156 0.0372 C -0.00054 0.3195 C -0.00038 0.427 AR(1) 0.121313 0.0000 AR(1) 0.145726 0.0000 AR(1) 0.246159 0.0000 Variance Equation C Variance Equation 5.61E-05 0.0002 C Variance Equation 2.86E-05 0.0000 C 1.11E-05 0.0006 RESID(-1)^2 0.239319 0.0000 RESID(-1)^2 0.220188 0.0000 RESID(-1)^2 0.175032 0.0000 GARCH(-1) Footer Page 187 of 89 0.728945 0.0000 GARCH(-1) 0.738369 0.0000 GARCH(-1) 0.788232 0.0000 Header Page 188 of 89 178 Ph lc Kt qu c lng mụ hỡnh CCC Cỏc phng trỡnh trung bỡnh: RCII = -0.00125401047294+0.0839002961242*RCII(-1) +e RFPT = -0.00160353921984+0.0605581155104*RFPT(-1)+e RGMD = -0.00253729651678+0.0860966474515*RGMD(-1)+e RKDC = -0.00101797052893+0.10143705969*RKDC(-1)+e RITA = -0.00207396143231+0.078632313595*RITA(-1)+e RVNINDEX=-0.000735170643729+0.119094618122*RVNINDEX(-1)+e Cỏc phng trỡnh phng sai: GARCH1 = 0.000105455532449 + 0.278904449294*RESID1(-1)^2 + 0.664381961928*GARCH1(-1) Prob (0.000) (0.000) (0.000) GARCH2 = 9.2133004015e-05 + 0.325559387907*RESID2(-1)^2 + 0.576824849594*GARCH2(-1) Prob (0.000) (0.000) (0.000) GARCH3 = 8.41890841123e-05 + 0.292234766559*RESID3(-1)^2 + 0.672738965563*GARCH3(-1) Prob (0.000) (0.000) (0.000) GARCH4 = 6.4231402351e-05 + 0.265810362863*RESID4(-1)^2 + 0.691411014647*GARCH4(-1) Prob (0.000) (0.000) (0.000) GARCH5 = 0.000132476015096 + 0.253438220487*RESID5(-1)^2 + 0.667809573438*GARCH5(-1) Prob (0.000) (0.000) (0.000) GARCH6 = 3.73793471141e-05 + 0.174654311498*RESID6(-1)^2 + 0.748735668436*GARCH6(-1) Prob (0.000) (0.000) Cỏc phng trỡnh hip phng sai: COV1_2 = 0.498282334165*SQRT(GARCH1*GARCH2) Prob Footer Page 188 of 89 (0.000) (0.000) Header Page 189 of 89 179 COV1_3 = 0.526742671525*SQRT(GARCH1*GARCH3) Prob (0.000) COV1_4 = 0.445011987939*SQRT(GARCH1*GARCH4) Prob (0.000) COV1_5 = 0.51451364586*SQRT(GARCH1*GARCH5) Prob (0.000) COV1_6 = 0.660144651063*SQRT(GARCH1*GARCH6) Prob (0.000) COV2_3 = 0.554149302091*SQRT(GARCH2*GARCH3) Prob (0.000) COV2_4 = 0.4600654794*SQRT(GARCH2*GARCH4) Prob (0.000) COV2_5 = 0.497339740627*SQRT(GARCH2*GARCH5) Prob (0.000) COV2_6 = 0.725294839971*SQRT(GARCH2*GARCH6) Prob (0.000) COV3_4 = 0.472885962835*SQRT(GARCH3*GARCH4) Prob (0.000) COV3_5 = 0.591013694372*SQRT(GARCH3*GARCH5) Prob (0.000) COV3_6 = 0.727263011566*SQRT(GARCH3*GARCH6) Prob (0.000) COV4_5 = 0.45871954421*SQRT(GARCH4*GARCH5) Prob (0.000) COV4_6 = 0.614401341392*SQRT(GARCH4*GARCH6) Prob (0.000) COV5_6 = 0.705111683562*SQRT(GARCH5*GARCH6) Prob Footer Page 189 of 89 (0.000) Header Page 190 of 89 180 Ph lc th cỏc chui phng sai cú iu kin garchrvnindex garchrhnx 0020 garchrita 005 05 0016 004 04 0012 003 0008 002 03 0004 02 001 0000 01 000 250 500 750 1000 1250 250 500 Conditional variance 750 1000 00 1250 250 500 Conditional variance 750 1250 garchrgmd garchrfpt garchrcii 016 05 035 1000 Conditional variance 014 030 04 012 025 010 03 020 008 015 02 006 010 004 01 005 002 000 00 000 250 500 750 1000 250 1250 500 750 1000 250 1250 500 Conditional variance 750 012 0018 0016 0020 1250 garchrctg garchrbvh garchrkdc 0024 1000 Conditional variance Conditional variance 010 0014 008 0016 0012 006 0010 0012 0008 0008 004 0006 002 0004 0004 000 0002 0000 250 500 750 1000 1250 100 200 300 400 500 600 700 100 800 200 300 Conditional variance Conditional variance 400 500 600 700 800 Conditional variance garchrdig garchreib garchrdpm 06 008 0024 05 007 0020 006 04 0016 005 03 004 0012 003 02 0008 002 01 0004 00 100 200 300 400 500 600 Conditional variance Footer Page 190 of 89 700 800 001 000 0000 250 500 750 Conditional variance 1000 1250 100 200 300 400 500 Conditional variance 600 700 Header Page 191 of 89 181 garchrhpg garchrhsg garchrhsg 024 006 006 020 005 005 016 004 004 012 003 003 008 002 002 004 001 001 000 000 000 250 500 750 1000 1250 250 500 Conditional variance 750 250 1000 garchrmbb 750 1000 Conditional variance Conditional variance garchrmsn 0024 500 garchrogc 0020 0035 0030 0020 0016 0025 0016 0012 0020 0012 0015 0008 0008 0010 0004 0004 0005 0000 0000 50 100 150 200 250 0000 100 200 300 Conditional variance 400 500 600 700 100 200 Conditional variance 400 500 600 garchrvcb garchrsbt garchrpvf 300 Conditional variance 0040 0040 007 0035 0035 006 0030 0030 0025 0025 0020 0020 0015 0015 0010 0010 0005 0005 005 004 003 002 001 0000 0000 250 500 750 Conditional variance Footer Page 191 of 89 1000 000 250 500 750 Conditional variance 1000 100 200 300 400 500 600 Conditional variance 700 800 Header Page 192 of 89 182 Ph lc Mt s chng trỡnh Matlab % c lng VaR v ES bng mụ hỡnh GARCH-EVT-copula load('data') T = size(data,1); nIndices = size(data,2); for i=1:nIndices spec(i) = garchset('Distribution' , 'T' , 'Display', 'off', 'VarianceModel', 'GARCH', 'P', 1, 'Q', 1, 'R',0) end residuals = NaN(T, nIndices); % preallocate storage sigmas = NaN(T, nIndices); for i = 1:nIndices [spec(i) , errors, LLF, residuals(:,i), sigmas(:,i)] = garchfit(spec(i), data(:,i)); end residuals = residuals / sigmas; % # of sampled points of kernel-smoothed CDF nPoints = 200; tailFraction = 0.1; % Decimal fraction of residuals allocated to each tail OBJ = cell(nIndices,1); % Cell array of Pareto tail objects for i = 1:nIndices OBJ{i} = paretotails(residuals(:,i), tailFraction, - tailFraction, 'kernel'); end U = zeros(size(residuals)); for i = 1:nIndices U(:,i) = OBJ{i}.cdf(residuals(:,i)); % transform margin to uniform end %[R, DoF] = copulafit('t', U, 'Method', 'ApproximateML'); % fit the copula RHOHAT = copulafit('Gaussian',U);%fit the copula-Gaussian s = RandStream.getDefaultStream(); reset(s) nTrials = 5000; % # of independent random trials % VaR forecast horizon horizon = 1; % standardized residuals array Z = zeros(horizon, nTrials, nIndices); %U = copularnd('t', R, DoF, horizon * nTrials); % t copula simulation U = copularnd('Gaussian', RHOHAT, horizon * nTrials);% Gaussian copula %simulation for j = 1:nIndices Z(:,:,j) = reshape(OBJ{j}.icdf(U(:,j)), horizon, nTrials); end preResidual = residuals(end,:) * sigmas(end,:); % presample model residuals % presample volatilities preSigma = sigmas(end,:); % presample returns preReturn = data(end,:); simulatedReturns = zeros(horizon, nTrials, nIndices); for i = 1:nIndices Footer Page 192 of 89 Header Page 193 of 89 183 [dummy, dummy, simulatedReturns(:,:,i)] = garchsim(spec(i), horizon, nTrials, Z(:,:,i), [], [], preResidual(i), preSigma(i), preReturn(i)); end simulatedReturns = permute(simulatedReturns, [1 2]); cumulativeReturns = zeros(nTrials, 1); weights = repmat(1/nIndices, nIndices, 1); % equally weighted portfolio %weights=[1/5;1/5;1/5;1/5;1/5]; for i = 1:nTrials cumulativeReturns(i) = sum(log(1 + (exp(simulatedReturns(:,:,i)) - 1)* weights)); end VaR = 100 * quantile(cumulativeReturns, [0.05 0.01]'); ys=sort(cumulativeReturns); %ES1=100*ys(50); %THU2=100*ys(250); ES5= mean(ys(1:250)); ES1= mean(ys(1:50)); ***** % c lng mụ hỡnh GARCH-copula: Dynamic Copula Toolbox Footer Page 193 of 89 ... TỔNG QUAN VỀ ĐO LƯỜNG RỦI RO VÀ THỰC TRẠNG ĐO LƯỜNG RỦI RO TRÊN THỊ TRƯỜNG CHỨNG KHOÁN VIỆT NAM Chương giới thiệu rủi ro mô hình đo lường rủi ro Trên sở tổng quan mô hình đo lường rủi ro phương... luận án Trên sở tổng quan mô hình đo lường rủi ro, luận án nghiên cứu ứng dụng số lớp mô hình đo lường rủi ro thị trường chứng khoán Việt Nam: Mô hình dự báo độ biến động, mô hình CAPM, mô hình. .. quản lý rủi ro tài cách chủ động hiệu Đề tài: Một số mô hình đo lường rủi ro thị trường chứng khoán Việt Nam nhằm tìm cách tiếp cận đo lường, đánh giá rủi ro thị trường chứng khoán Việt Nam Mục