panel GARCH EGARCH 3 EGARCH - -
4. 4. 5.. LIQUIDITY 5.. MANAGERIAL PERFORMANCE THEORY 5..3 INVESTOR SENTIMENT THEORY RATIONAL EXPECTATION THEORY 6..4 MARKET FRICTIONS 6.3 7 8. 8. 8.. 8.. 9.3.3..3. 3 3 4 3. 4 3. 6 3.3 8 4 - -
4. 4.. 4.. 4. 4 4.3 EGARCH 5 4.3. 6 4.3. 7 4.3.3 8 4.3.4 9 5 3 35 37 3 37 8 37 3 38 4 39 5 4 6 6 EGARCH 44 7 EGARCH 45 8 EGARCH 46 9 47 47 6 47-3 -
. closed-end fund NAV pricei NAVi D i = NAV i. LeeShleifer Thaler99-4 -
3... liquidiy proxy for liquidiy Daar.. managerial performance heory sock selecion marke iming Chay Trzcinka999-5 -
..3 invesor senimen heory raional expecaion heory DeLongShleiferSummers Waldmann99 noise rader LeeShleifer Thaler99 DSSW, Chandar Paro closed-end counry funds Kyle985 O Hara 997..4 marke fricions raional explanaion - 6 -
.3 panel GARCHEGARCH 3 EGARCH - 7 -
. 3 3 ) % 6 5 ) % 4693 4695 49.37%5.97% 3) 58 59 58 Skewness 4693 9.4 4) 3 9 lepokuric (playkuric) 4693... - 8 -
n D D = α + β + ε. D D D = a + ) D ( β + ε. ε β = D DickeyFuller β = 9 8 8 ) ) D + ε = D 3) 57 D.. D i Pi NAV i = NAV i W i n i = NAV i NAV Pi i = m i i m i, DI = n i = W i NAVi i Di i mi Wi i n DI D i, - 9 -
999 9 8...3.. 999 99958 9998 5 77 7 46 87 -. -. -.3 99 999 5.. - -
.4.3.. -. 7 33 49 65 8 97 3 -. -.3 98 5 3%. 999 5 3 3 9 8 3 A.3.4.3.5..5..5 -.58 4 6 8 -. -.5..5 4 5 6 7 8 9 -.5 -. -.5 -. -.5.3.4 - -
3 999 4 4 4 999 4.3 (invesor senimen) DeLongShleiferSummers Waldmann(99), LeeShleifer Thaler(99)DSSW :,.3. 999 9 7 58 59 5% - -
.3. Likelihood Raio 4688. 4688 4689 469 469 5 5 53 55 56 58 59 4689.93. 469 6.7*.*. 469 9.73*.9*.9*. 5 7.5* 3.86*.97* 9.4*. 5 5.6*.5 5.33 5.5* 8.3*. 53 5.4.3 7.96* 9.53* 8.3*.9. 55 5.68* 6.63*.53*.* 4.*.66 9.. 56.84 5.76* 4.37 5.86* 5.55*.9 9.39* 6.66*. 58.43 4.43 4.58.39.7.4 9..5.35. 59.83.4.5 8.35* 5.36.5 9.87.3.58 8.75 * 5%.3..6 3-3 -
3 3. privae informaion noise ( v N p,σ (, σ ) N ~ v ) - 4 -
O Hara(997) Single-Aucion Model agen v x x + p p x + p = P x + π = ( v p) x P ( ) ( x + ) = E[ v x + ] ( ) X o X (O) v E [ π ( X () o, P) v~ = v] > E[ π ( X ( o), P) v~ = v Kyle Kyle985 () v = β ( v p ) = α + βv x = X 3. α = βp ( x + ) = p + λ( + ) P = P x 3. β = Σ σ λ = Σ σ ] - 5 -
3. laws of condiional disribuions of normally disribued random variables ~v ϑ ~ γ ( ~ N, σ ) ( ϑ ~ N ~,Σ ) E() v p ( ) = x + α + βp ~ γ x + ~ = E Σ Σ Σ Σ βσ = = Σ Σ βσ σ + β Σ λ = βσ σ + β Σ P( x + ) = E = p = p ( ) ( ) ( vγ ) = + Σ Σ ( γ ) βσ + σ + β Σ + λγ ( γ α βp ) 3.3 ~ π = E = ( v ~ d ~ π = dβ σ β = ( ) λ = Σ σ {[ v P( x + ) x] v = v~ } = E{ [ v ( P )] x v v~ + λγ = } β x P ) x σ + β / x( σ + β ( σ + β ) β ) ~ π ) x x σ β x = ( σ + β x x σ β = 3.3 Σ E ~,Σ ( ) () ( ) ϑ = ϑ,ϑ N Σ () ( ) () ( ) ( ) ( ϑ ϑ ) = + Σ Σ ( ϑ ) - 6 -
( x + ) = p + λ( x + ) P ( v) = ( v ) x = X β θ x + = v p + = β ( ) p θ β + p = v + β 3.4 β Z θ β + p = v + Z v ( σ ) Z, ( v, ) Z v ~ N β σ N ~ Z v Bayes Learning Rule p p = p Σ + Z ( β σ ) Σ + β σ ( Σ + β σ ) Σ = β pσ + σ Z p = = β + σ + σ ( p + Z ) = ( p + θ p ) θ = x + λ = Σ p = p = p σ x + + β σ + Σ ( x + ) = p + λ( x + ) x = β ( v p ) - 7 -
x = Σ σ ( v p ) 3.5 x π = E [( v P ] ( ) ) x = Σ σ 3.6 σ 3.3 λ x p x densiy p convoluion σ / σ p ( ) + = p + v p 3.7 σ Σ Σ p p v - 8 -
Σ = Σ β + σ β Σ = Σ σ σ + σ = Σ 3.8 v 5% p v v p ( ) N p,σ N ( p Σ ) 3.7 v, p [ p v] ( p ) E = + 3.9 v v v 3.4 θ β + p = v + β β T θ + T p = v + T = T = β T = T 3. T Srong Law of Large numbers E T T = T θ T T T = p = v T [ p v] E[ p v] = lim p v = T T = - 9 -
v - -
4 4. 4.. 45 999 Yi =a+agmi+ajyri+a3fhi+a4jzdi+a5idxi+a6vi+a7kmxsi+i (4.) Y. ε i GM 3, ) JYR ) FH 3) JZD % - -
% % % 4. 4 JZD = I d + I d +... + I d i i 4. I i d i 4) IDX 5) V 6) KMXS 4.. 5: Variable Number Parial Model 4. Sep Enered Label Vars In R-Square R-Square C(p) F Value Pr > F GM GM.337.337 78.693 9.6 <. JYR JYR.684.454 46.4949 9. <. 3 FH FH 3.763.487.365 37.4 <. 4 JZD JZD 4.3.4949 5.79 6.59.9 5 IDX IDX 5.37.4985 5.8893.83.77 6 V V 6.38.53 6.4.89.699 - -
4. Parameer Sandard Variable Label DF Esimae Error Value Pr > GM GM -.4596.4983-9. <. JYR JYR -.33643.4867-6.9 <. FH FH.37.467 6.44 <. JZD JZD -.5.4865 -.57.7 Y =.585.7859GM.4378log( JYR) +.36FH. 3384JZD i i i i ) ) 3),,,,,, 3-3 -
4. 4) 4.3 4. 999 5 3 3 9 3 3 4.3 (999 ) Parameer Sandard Variable Label DF Esimae Error Value Pr > Inercep Inercep -.74.66-4.34 <. IDX IDX -.3774.7585-4.6. GM GM.86.93.6.95 FH FH -.33.775 -.7.939 JZD JZD -.96.336 -.68.7-4 -
4.4 3 9 Parameer Sandard Variable Label DF Esimae Error Value Pr > GM GM -.435.5668-7.63 <. FH FH.33896.496 6.83 <. JYR JYR -.359.5645-6.4 <. JZD JZD -.998.665-3..8 3.3774P. A,,,,, A 4.3 EGARCH 985 Kyle - 5 -
Kyle,985 4 BreadhWidh (Deph) 3 Resiliency 4 (Immediacy) 3, 4.3. 53 56.. - 6 -
6 6 4.3. GARCH ---EGARCH EGARCH Nelson(99)GARCH, 976 98 Black Chrisie (Leverage Effec) h ε i Nelson99 GARCH EGARCH EGARCH h ε. i R = i= γ R i + ε log( h ) = var( ε ) = a + r z = ε / i h q i= a log( h i ) + λ p i i= z - + θ p i i= z - 4.3 EGARCHM R γ + h Z 4.4 = c + R + βv + β V + β 3V3-7 -
3 = a + ( a j ln h j + λ j Z j + θ jz j ) + ϖ V + ϖ V + ϖ 3V + ξ j= ln h 3 R ln P ln P lnt4.5 P V V V 3 T h Z 4.3.3 6 EGARCHM 68 ) R R-.3.5 ) V 97 6 97 676.7 6.4 68.38 6 685.8 3) (V3) 4 4) θ RES/SQR[GARCH]()RES/SQR[GARCH]() RES/SQR[GARCH](3) θ - - 8 -
- 5) 6 89 T 86 89 V3 4.3.4 dv P d ln EGARCH-M Z h Z V h h dv P d ln ϖ β β + = + = 4.6 h Z ) ln ( β = dv P d E ) ( 4 ) ln ( h E dv P d D ϖ = 4.7 ) ( 4 h E ϖ n i i i dv P S d ) ln( = V S i i i V V χ = i χ i i i n i i i i n i i i i n i i n i i i dv P d P S dv P d P S dv dp S dv P S d ln ln χ = = = = = = = 4.8-9 -
χ i S i i = n i= S P i P i d dv n i= S i P i / n i= S i P i d ln P n i = χ i i= dvi d ln n S P d ln P = 4.9 i i n n i= i E( ) E( χ i ) E( ) = χ i β i dv i= dvi i= n d ln Si Pi n n i= 4 d ln Pi 4 D( = χ i D = χ i wi E( hi ) dv dv 4 i= 4.9 4.8.76 9.87.36 6 i i= - 3 -
5-3 -
Sharpe Jensen Treynor - 3 -
- 33 -
3. - 34 -
. Alan K. Severn, 998, Closed-end funds and senimen risk, Review of Financial Economics 7, No..3-9.. Bollerslev T., 986, Generalized auoregressive condiional heeroskedasiciy, Journal of Economerics 3, 37-37. 3. Brauer, Gregory, 998, A closed-end fund shares abnormal reurns and he informaion conen of discouns and premiums, Journal of Finance 43, 3-8. 4. Charles M.C. L, Anderei S. and Richard H.T, 99, Invesor senimen and he closed-end fund puzzle, Journal of Finance, Vol XLVI. 5. Chay J.B. and Charles A.T., 999, Managerial performance and cross-secional pricing of closed-end fund, Journal of financial economics 5, 379-48. 6. Chen Nai-fu, Raymond K., Meron H and Miller, 993, Are he discouns on closed-end funds a senimen index?, Journal of Finance 48, 795-8. 7. De Long, J.B., Shleifer A., Summers L. H., and Waldmann R. J., 99, Noise rader risk in financial markes, Journal of Poliical Economy 98, 73-738. 8. Dilip K.P.,, Measuring performance of he inernaional closed-end fund, Journal of Banking and Finance 5, 74-76. 9. John E. Richard, James B. Wiggins,, The informaion conen of closed-end counry fund discouns, Financial Services Review 9, 7-8.. Kyle, A.S., Coninuous aucions and insider rading, 985, Economerica 53, pp35-336.. Lee, Charles MC., Shleifer A. and Thaler R. H., 999, Invesor senimen and he closed-end fund puzzle, Journal of Finance 46, 75-9.. Maddala G.S., 998, Inroducion o economerics, nd Ediion. 3. Chandar N. and Paro D. C., Why do closed-end counry funds rade a enormous premiums during currency crises?, Pacific-Basin Finance Journal 8, 7-48. 4. Neal R. and Whealey S.M., 998, Adverse selecion and bid-ask spreads: evidence from closed-end Fund, Journal of Financial Marke,-49. - 35 -
5. O Hara and Maureem, Marke microsrucure heory, 997, Blackwell Publishers Inc. 6. Olienyk J.P., Schwebach R.G. and Zumwal J. K., 999, WEBS, SPDRS, and Counry Funds: an analysis of inernaional coinegraion, Journal of Mulinaional Financial Managemen 9, 7-3. 7. Daar V.,, Impac of liquidiy on premia/discouns in closed-end funds, The Quarerly Review of Economics and Finance 4, 9-35. 8. 7 9.. - 36 -
3 5 5 53 55 56 57 58 59 5 5 55 56 58 5 55 535 -.% -.53% -8.67% -.8% -7.83% -6.7% -9.36% -4.8% 3.35%-4.79%-.9%-.6%-.75%.89% 53.5% 8.9% -.65%-5.3% -9.59% -.% -8.73% -.% -9.% -4.93%.76%-5.56%-.96% -8.96%-3.%.87% 46.6% 5.77%.7 8..97 69.3 79.37.53 36. 68.44 35. 44.99 55.9 7.37 33.6 33.4 35.43 79..54% 9.%.5% 8.33% 8.9%.8% 6.% 8.7% 5.9% 6.7% 7.43% 8.5% 5.77% 5.78% 7.76% 8.89% -4.39%-5.53%-4.9%-4.79%-.44%-.86%-.9%-36.3% 3.46%-5.5%-3.6%-8.3%-3.5% -6.7% 9.87% 6.85% 6.4% 3.% 6.8% 4.76% 9.77% 4.35% -.9% 7.4% 6.66%.%.46% 6.39% -5.% 8.3% 9.7% 47.3% 5.53% 8.53% 5.7% 39.55% 5.% 36.% 9.% 43.7% 3.9% 6.6% 5.7% 44.7% 8.5% 34.39% 6.4% 4.38%.35.3.738.358.59.5 -.345 -.45.63.45.6.35 -..68.343.863 3.58 -.44.568.88 6.76 -.39 -.97.5 -.94 -.658 -.77.7 -.8.39 -.8 4.83 4688 4689 469 469 469 4693 4695 4696 4698 4699 47 47 473 475 478-8.54% -.5% -.6% -.3% -.3% -6.5% 6.49% 6.43% -4.55%-3.9%-3.93% 8.7% 9.57% 8.64%.3% -9.9% -.9%-3.68%-.6%-.84%-.7% -7.33% 6.3% -4.8%-3.57%-4.79% 6.6% 8.66% 7.33%.% 4.7 79.75 88.75 76.5 64.43 437.88 674.4.5 49. 8.53 43.73 48. 3.56 33.57 45..% 8.93% 9.4% 8.75% 8.3% 49.37% 5.97% 3.4% 7.% 5.34% 6.6% 6.93% 5.7% 5.79% 6.7% -3.74%-5.4%-5.86%-3.79%-4.77%-6.38%-3.% -.7% -5.93%-3.3%-3.99% 9.66%.6%.% 4.5% 3.97% 3.55% 8.5% 8.45% 5.85% 473.% 54.%.99% 7.%.37%.84% 35.99% 3.6%.86% 38.5% 55.7% 48.96% 44.% 4.4% 4.6% 499.6% 77.4% 3.7% 33.5% 5.69% 6.83% 6.33% 3.%.85% 34.%.83.6.86.488.454 9.4.6.3.355.69.354.99.486.8.6 4.363 4.637.735.9.58 9.64 -.67 -.88.5.467 -.333.53 4.36 -.44 6.6 8 4688 4689 469 469 469 4695 4696 4698 4699 47 47 473 475 478 Level -.69 -.4 -.8 -.67 -.49 -.4 -.73 -.4 -.3.9 -.84 -.57 -.85 -.63 T- -3.48-3.49-3.49-3.49-3.5-3.5-3.54-3.5-3.5-3.5-3.54-3.55-3.54-3.56-6.65* -6.39* -5.86* -7.5* -6.55* -.9* -5.43* -6.57* -7.44* -5.58* -.98-4.93* -5.84* -3.88* T- -3.48-3.49-3.49-3.49-3.5-3.5-3.54-3.5-3.5-3.5-3.54-3.55-3.54-3.56 5 5 53 55 56 57 58 59 5 5 55 56 5 55 Level -.5 -.93 -.43 -.8 -.83.65 -.58.9 -.38 -.3 -. -.4 -.36 -.6 T--3.48-3.49-3.48-3.49-3.48-3.5-3.48-3.49-3.55-3.5-3.5-3.5-3.56-3.57-6.86* -4.7* -5.95* -6.9* -7.43* -.89-7.6* -5.3* -5.34* -6.* -5.34* -3.6-6.3* -6.5* T--3.48-3.49-3.48-3.49-3.48-3.5-3.48-3.5-3.56-3.5-3.5-3.5-3.56-3.57-37 -
3 D5 D5 D53 D55 D56 D58 D56D57 D59 D5D55 D58 D4688 D4689 D469 D469 D469 D4693 D4695 D4698 D4699 D47 D5 D5.746 D53.4655.3997 D55.5365.448.799 D56.4749.36.734.944 D58.339.3.7.594.69 D56.496.399.7466.88.743. D57.55.457 -.96 -.9 -.45.548 -.85 D59.35.75.597.6.567.949.5653 -.785 D5.789.8553.3996.3935.786.354.3545.46737.897 D55.4869.575.738.897.6945.474.6967 -.69.589.5488 D58.63.57.39.958.969.3.89.668.366.4867.4888 D4688.56.48.7598.949.956.56.7666 -.493.5967.496.739.647 D4689.57.4834 -.39.99.4.56 -.68.845 -.7.495 -.6.77 -.9 D469.933.855.5.58.3986.6.4578.533.334.873.53.33.484.59 D469.3663.68.789.97.355.685.539.6.78.44.83.7.47.56.34 D469.3533.9.68.656.697.4.685 -.75.47.99.54.485.643 -.58.3735.96 D4693 -.37 -.94 -.69 -.69.5.5 -.36 -.3355 -.74 -.37 -.6.5 -.57 -.8 -.43 -.53 -.6 D4695.338.78 -.84 -.5 -.8.95 -.84.58968 -.89.347 -.55.77 -.75.5465.39.783 -.753 -.38 D4698.4434.56.779.856.785.397.7889 -.388.534.5359.88.49.887 -.49.498 -.8.6 -.67 -.787 D4699.388.557.99.464.4346.387.87.36.485.5497.46.6.43.546.6.7.59 -.47.86.859 D47.58.553 -.53 -.69 -.33.46 -..87 -.9.654.588.343 -..783.5399.96 -.356 -.584.5586 -.68.365-38 -
4 98/6/3 98/9/3 98//3 99/3/3 99/6/3 99/9/3 99//3 /3/3 /6/3 /9/3 //3 /3/3 /6/3 /9/3 4688 9.69 4.95 4.3.8 6.57 5.3 6. 7.9 7.78 3.4 3.3 3.57 3.5.39 4689.36 4.5 4. 3.93 3.4.37.3.5.7.7. 469.44..5 5.3 3.9.45.47.8.8.5 469 5.65 3.44 3.73 4.4.59.7.9.4.7.6 469 3.55.7 4.49 3.93 3..7 3.7.46.94 4693.4.7.8.9.95.79.73.79.46 4695.3.3 3.9.85.59.3.36 4696.78.3.57.5.5. 4698 3.63 5.6.75 4.64 4.6 4.5 3.99 3.5 4699.7.36.59.5.7.47.79 47 3.7..9.54.86.5.73 47.6.39.74.36.6. 473.84.9.58.54.75 475.3.7.9.54.59.37 476.49 478.34.56.36.33.8 47.85.9.7.93 47.5 47.. 473.39.43 478.39.37.65.96.7 4738. 5.8.44.9.8.9.. 3.7 4.9 3..3.4.58. * 5.4.5.47.6.44.4.47.54.6.53 53.5.66.3 5.66 6.5 5.89 4.4 4.6 3..9 3.9.4.75 55 4.4 5.39 4.73 5.47.83.6.33.67.3.87 56.46 5.9 4.73 5.36 6.9 5.4 4.87 4.47 3.9 3.7.58.3.53 57 3.7.99.6.45.69.88.67 58.99.67 7.6.5 6.4 5.73 5.37 7.73 3.86.87.8.67.5.49 59 3.6..87.96 4.8.65 3..33.57 5.5.74.7.3.98 5.4.5.7.37.57.3.83.75 55 3.5 3.73 3.47 3.54.5.5. 56.98.78.7 3.6.7 3.4. - 39 -
58.4.46.39.4.9.33.. 7.7 59. 5.4.86..5.96 55.4.76.45 5..37 58. 59.6.9 535.37.4.4.3 539.7-4 -
5 The REG Procedure Model: MODEL Dependen Variable: Y Y Forward Selecion: Sep Variable GM Enered: R-Square =.337 and C(p) = 78.693 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 86.757 86.757 9.6 <. Error 55 69.7473.66559 Correced Toal 56 56. Parameer Sandard Variable Esimae Error Type II SS F Value Pr > F Inercep 6.7393E-.589.5847E-6.. GM -.5853.599 86.757 9.6 <. Bounds on condiion number:, Forward Selecion: Sep Variable JYR Enered: R-Square =.454 and C(p) = 46.4949 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 3.7749 5.8879 86.58 <. Error 54 5.58.5993 Correced Toal 56 56. Parameer Sandard Variable Esimae Error Type II SS F Value Pr > F Inercep 5.967E-.489 9.557E-7.. GM -.496.57 55.68745 9.9 <. JYR -.7595.57 7.4989 9. <. Bounds on condiion number:.4, 4.4559-4 -
Forward Selecion: Sep 3 Variable FH Enered: R-Square =.487 and C(p) =.365 Model 3 3.3463 4.54 78.37 <. Error 53 3.69537.5449 Correced Toal 56 56. Parameer Sandard Variable Esimae Error Type II SS F Value Pr > F Inercep.845.458.856..985 GM -.585.4779 57.5977 9.8 <. JYR -.34636.495 6.4957 49.67 <. FH.868.47 9.5344 37.4 <. Bounds on condiion number:.79,.95 Forward Selecion: Sep 4 Variable JZD Enered: R-Square =.4949 and C(p) = 5.79 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 4 6.68469 3.677 6.7 <. Error 5 9.353.536 Correced Toal 56 56. Parameer Sandard Variable Esimae Error Type II SS F Value Pr > F Inercep.884.4468.9958..9843 GM -.4596.4993 43.483 84.74 <. JYR -.33643.4877 4.49 47.59 <. FH.37.468.88 4.8 <. JZD -.5.4875 3.386 6.59.9 Bounds on condiion number:.437, 8.84-4 -
Forward Selecion: Sep 5 Variable IDX Enered: R-Square =.4985 and C(p) = 5.8893 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 5 7.69 5.5438 49.9 <. Error 5 8.3788.547 Correced Toal 56 56. Parameer Sandard Variable Esimae Error Type II SS F Value Pr > F Inercep.9658.446.59..9836 IDX -.6767.4999.9373.83.77 GM -.474.556 44.39833 86.8 <. JYR -.3769.56.49 39.39 <. FH.377.4757.9 43.3 <. JZD -.4555.596 4.73 8.6.46 Bounds on condiion number:.996, 3.86 Forward Selecion: Sep 6 Variable V Enered: R-Square =.53 and C(p) = 6.4 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 6 8.5874.434 4.5 <. Error 5 7.458.5965 Correced Toal 56 56. Parameer Sandard Variable Esimae Error Type II SS F Value Pr > F Inercep.93645.4453.537..983 IDX -.885.55.46797.88.99 GM -.4645.594 4.8444 8.5 <. JYR -.8933.5457 4.377 8. <. FH.3955.4774.8344 44.8 <. JZD -.3.547.5398 4.95.69 V -.87.5936.9655.89.699 Bounds on condiion number:.77, 5.46 No oher variable me he.5 significance level for enry ino he model. - 43 -
6 6 EGARCH 68 89 68 685 67 c 639 6555 6637 685 (6) P P P P P P P P P P R(-) -.4. -.356. -.49. -.43. -.35. -.4. -.39. -.367. -.44. -.38. V.3..96..39..9..337..8..435..579..63..797. V -.3. -.5. -.9. -.8. -.37. -.5. -.97. -.. -.344. -.8. V3 -.4. -.54...83.. -.89. -.38. -.67. C -.7. -.476. -.33. -.939. -.335. -.55. -.3. -.3. -.38. -.539. RES /SQR[GARCH]().45..489.383..443..3879..585..3758..37..396..374. RES/SQR[GARCH]().4..48..9. -...96.55.59..76..6.5 -.4.65 -.33. RES /SQR[GARCH](). RES/SQR[GARCH](). RES /SQR[GARCH](3). RES/SQR[GARCH](3). EGARCH().938..7759..86..578..448..77..96..547..493..8538. EGARCH().......9..49. -.59...347..3794.. EGARCH(3)..7. T.99..867..5. -...979..73....676..446..53. V.95..79..834..6..89..7..87..79.... V.97..85..463..793..777..64..687..734..7..733. V3.57..56..47..436..99..7..537..37..5..7. - 44 -
7 EGARCH 4 554 68 73 89 68 677 698 676 685 () P P P P P P P P P P R(-) -.39. -.39. -.45. -.4. -.36. -.43. -.43. -.4. -.3. -.4. V.3....6..6..8..3..3....7..3. V -.7. -.4. -.38. -.35. -.. -.9. -.3. -.3. -.9. -.33. V3 -.4. -.4. -.7. -.7. -.7. -.9. C -.46. -.4. -.37. -.4. -.33. -.56. -.56. -.5. -.77. -.5. RES /SQR[GARCH]().4..4..39..4..37..7..8..49..37..4. RES/SQR[GARCH]().8. -..5 -.3. -.4. -.4..3..3...94.5.4 -.3. RES /SQR[GARCH]().7..7..3. RES/SQR[GARCH]() -.4. -.4..3.7 RES /SQR[GARCH](3) RES/SQR[GARCH](3) EGARCH().43..48..6..5..4..35..35..38..3..5. EGARCH().3..39..6..34..5..43..43..45..45... EGARCH(3) T.4..6....8. -...6..6....33..5. V.....5..9. -.3......7..34..5. V.5..3..8....8......3....6. V3.3..4......5..3..3....4..9. - 45 -
8 EGARCH () 53 636 86 97 96 6 635 698 678 6747 P P P P P P P P P P R(-) -.4. -.4. -.46... -.39. -.43 -.387 -.39. -.34. -.35. V.9....5. -.....4.74.4..36..3. V -.7. -.. -.3..3. -.6. -.6 -.88 -.6. -.7. -.3. V3 -..37.. -.5. -.4.7 -.4. -.5. C -.4... -.4. -9.48. -.44. -. -.58 -.5. -.6. -.34. RES /SQR[GARCH]().4....48..6..36..53.4889.49..44..37. RES/SQR[GARCH]() -..7.. -.8..7. -.. -..8.486..49 -.4. RES /SQR[GARCH]()...35..4..9..34.536.4..4. RES/SQR[GARCH]().. -...6. -.3. -..7.43. -.4. RES /SQR[GARCH](3).7 RES/SQR[GARCH](3) -.7 EGARCH().56..6..39. -.48..8..4.3..5. EGARCH().34..59..3..38..6...38..4. EGARCH(3).5 T.3..3..6..... -.3..75...9..44. V.5... -.8. -...6..33.543.8....5. V.7....87. -.....344.547.6..5..4. V3...8..6....9..44.3.8..35..3. - 46 -
9 Bea 53 4,85,36.96 6.3% -.79 533.488 636 33,968,738.53 9.3% -.63 43.335 86,95,36.5.89% -.58.393 97 75,99,37.49 4.9%.74E-5 4.56 96 38,957,93.6 6.7% -.638 353.9 6 47,869,47.85 4.5% -.693 465.977 635 5,533,75.96 7.3% -.8793 384.3 698 84,63,66.88.36% -.556 96.55 678 89,899,7.49 5.33% -.77 36.56 6747 94,547,96.43.65% -.899 6.68 -.76633 bea 4 7,9,4.4 4.3% -.7 67.4 554 9,8,65.3.34% -.4 939.85 68 5,79,499.6 3.3% -.38 589.79 73 3,53,383. 5.84% -.35 9.7 89 8,633,6.4 3.% -. 636.59 68 4,76,4. 5.46% -.9 69.53 677 8,4,. 3.5% -.3 45.7 698 6,366,5.36 5.4% -.3 446.97 676 9,95,69.8.33% -.9 5.6 685 4,9,389.89 3.59% -.33 36. 4.8 6 Bea 68 35,936,5.75. -.3 3677. 68 9,7,3..8 -.9 63.69 685 96,49,3.8.7 -.8 456.4 6637 54,65,7.6.5 -.34 378.63 639 47,946,964.88.5 -. 364.76 676,47,97.8.4 7.3 685,584,554.34.4 -. 963.6 6555 8,95,57.48.3 -. 86.7 67 7,3,.4.3 -.3 463. 89 7,6,4.. -. 859.5-6.866943 47