1、中国股票市场波动率的高频估计与特性分析*黄后川( 2Z5 null 510200)null陈浪南( v 4 2 v6 null 510275)null null = 41:本文旨在应用高频数据估计中国股市的已实现波动率b我们发现股票指数与个股的高频交易数据中的微观摩擦影响正好相反,使用极高频的数据会大大增加个股的波动率估计值,相反却会大大降低指数的波动率估计值b在计算各种频率的已实现波动率的基础上,本文构造了一种较为精确的估计波动率的方法,可以更好地平衡测量误差与微观结构误差b基于已实现波动率,本文研究了中国股市波动率不对称性和长期记忆特性b1oM:波动率null 高频估计null 特征* n
2、ull SE1 S 5( 79800010a70042005)a 2002 M 9 5aSnull Enull 5( 01jb790026)#2002 M0 vn) 5TBbBa5 - 5 = E M ,o q X 6 51 = Bb1Engle1982 M4ARCH ,6X?V $ 1HqsZo q b+YK E M,Bt4 s H 9o qZE,ZE V1 oq9,nullX LCo qnull ( Realized Volatility)bN$,o q+ Z ,vvZ 5bAndersenaBollerslevaDieboldaEbens( 1998, 2001) 6E 9ZE#null
3、X LCo qnull+ B“ , /+1 (9 o q o q) :( 1) TNN Y V,NZE9 X LCo q, b7 O, HWW t0 H,X LCo q 9 t0byN VX LCo qTB4, E HWb( 2)YV gnull j bY,6E HW s t M (1B V s, Y t BZE k HW iBbGranger( 1966)?Cv4 M i“1M1“ hC, 1 Ho q9,null21 = r2 = nullni= 1 ri2= null ni= 1 ri2 + nullni= 1 nulljnull irirj = null ni = 1 ri2 + 2
4、nullni= 1 nullnj= i+ 1rirj= null2n + 2 nullni= 1 nullnj = i+ 1rirj = null2n + 2 nullni= 1 nulln- ij= 1riri+ j ( 2): o q9= o q9+ 2null lm q W =1xZb6, null2 = null ni= 1 ri 29 V/ TV U:76+a 2:S“ go q 9+sE null ni = 1 ri2 - null2 2 = null4n (Ki - 1) 1 + 2 nulln- 1i = 1n - in nulli ( 3)null null Ki ri, n
5、ulli ri2i1M1“ (Karatzas, Shreve, 1988)b ( 3)T, A,9 “ q97, T1 o q9,Kz |K qKl HWWb7,“N HW ,N /Ki“ lm q 1M1“ , ( 2) T,yE( riri+ j ) b VYVs 81BM ( ( Fractional Integrated Autoregressing Moving Avnullerage,ARFIMA)z E !C HW b :k :kV VdBARFIMA Y, ARFIMA( p, d, q) T /:null( L) ( 1- L) dyt = null( L) nullt (
6、 5)null null yt V4 ( Yn q) , nulltB . 2 , null( L)anull( L)sYLpaq T, d Bs ,V U Tsbd= 0 H, ARFIMA( p, d, q) |ARMA(p , q) ,d= 1 H, ARIMA bZE V_9 :kVi#V1M d, P mZE9s 8 b mZEGPH9ZE, GewekeaPorternullHudak( 1983)4Bd mBZEbn5,19 HW q/ m: I( null) = | null nj= 1Xjejnulli | null( 2nullN) , i , null= 2nullknu
7、llN = qbyI( null) B9 , :kVI( null) | null| - 2d 1,/LZ:ln(I( nullk ) ) = null0 + null1ln sin2( nullknull2) + null9null1, d= - null1 V9 s 8 b s 8 9d9 A,5 o q :kb772003 M2 a Ls1null“ P S AaB“ 2000 M14 2002 M325 W = 3 b A“ 9252510H,c519 , ( 485H, B“ 9199106H,c513 , ( 388Hb W =s S V1 Ub表1 有异常的高频(每笔交易)数据列
8、表日期 数据 异常原因2000 null 03null 27至2000 null 03null 31 上证A指, 上证B指 缺失数据2001 null 02null 20至2001 null 02null 23 上证B指 暂停交易2001 null 02null 26至2001 null 02null 27 上证B指 暂停交易2001 null 05null 08 上证A指, 上证B指 缺失数据2001 null 11null 15 上证A指, 上证B指 缺失数据null null , 7 3 , 6,y B2000 M220 2000 M227 W T, B1 A1 6 bk ,t , V
9、HW h“b 6, Aa BWxZM1, V A“ 6 ,9 xZM1 ,yNxZM1 513b2nullK HWWo q9C LNi V ? V,yN9X LCo q H, HWWi lz, 9o qy4 7 3 vbTorben G. Andersen null j 30b VYVARFIMA E !C HW b mZE9ARFIMA s 8 b n5,19 HW q/ m: I( null) = | null nj= 1Xjejnulli | null( 2nullN) , i , null= 2nullknullN = qb :kVI( null) | null| - 2d 1,:ln
10、(I( nullk ) ) = null0 + null1ln sin2( nullknull2) + nullnull null9null1, d= - null1 V9 s 8 b s 8 9d9 A,5 o q :kb表3 上证AaB指波动率a相关度的长期记忆检验表样本数 Beta R2 d上证A 指波动率 22 - 0. 36544 0. 9128 0. 36544上证B指波动率 22 - 0. 28042 0. 9487 0. 28042AaB指相关度 22 - 0. 4453 0. 94422 0. 4453null nullY, E9 ln( I( nullk) ) ov, N
11、M ( MA5),LBs 8 b V3 U,L9R21 v, s 8 900null5W,V 3 HW (A :k+b Bo q s 8 0null28, Ao q#AaBM1 9, Bo q M ba S“ go q, 1 9a+(saa :k)# EZ bn5, ?C“ “ 4 YzMQ, P vv9F“o q9,MQ vv o q9by 4 H vM, 5s15s i V |, 4812003 M2 nullS:mnullZE9B ,/ B 9o qZE, AaB o q bQ,X LCo q, S“ go q :k+bo q+Z , AaB ( A lm lm,|LB Vz E;o q
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21、nulltics, University of Economics and Business Administration, Vienna, Austria.Henry O. 1998, null Modelling the Asymmetry of Stock Market Volatility,null Applied FinancialEconomics, 8, 145 null 153.Sowell F. 1992, null Maximum Likelihood Estimation of Stationary Univariate Fractionally Integrated T
22、ime Series Models,null Journal of Econometnullrics, 53, 165 null 188.(责任编辑:石null 村) (校对:林)82+a 2:S“ go q 9+sAnalysis on Character and Highnullfrequency Estimationin Chinanull s Stock MarketHuang Houchuan leverage effect; long memory effectJEL Classification: G100, C510TheMarket Liquidity of Contract
23、ing and Operating Right toRural Land: A Theoretical and Empirical StudyQian Zhonghao( Yangzhou University)The market liquidity of contracting and operating right to rural land ( MLCORRL) dependents on the effective rural land demandand supply. The impact of relative factors, such as land production
24、price, nonnullproductive return, productive cost, nonnullproductivecost, land price, transaction cost and land scale on rural land supply and demand were analyzed by decision model in MLCORRL,The conclusions followed: land demand exceeded the land supply as a whole and the market is faced the constraint of rural land denullmand, improvement on the external condition of the MLCORRL should be made to promotnullthe effective rural land supply.Key Words: Contracting and Operating Right to Rural Land;M arket LiquidityJEL Classification: Q150, Q12094
