:,,,,,, Engle 1982 ARCH,,,, (Realized Volatility),, Andersen Bollerslev Diebold Ebens(1998,2001), ( ) :

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1 003 3 ( ( 51075) 51000) :,,,,, : 3 ( ) 00 (01jb79006) 00, Egle 198 ARCH,,,, (Realized Volatility),, Aderse Bollerslev Diebold Ebes(1998,001), ( ) : (1),,, 0, 0, (), :,,,,, (3) (), (Auto Regressio Fractioal Itegrated Movig Average, ARFIMA) ( VaR),,,, ARCH Chia Academic Joural Electroic Publishig House. All rights reserved. 75

:,,,,, (3) (), (Auto Regressio Fractioal Itegrated Movig Average, ARFIMA) ( VaR),,,, ARCH

2 :, Egle Ng(1993), ( ),,,,,,,,,,,,, Grager (1966), ARIMA,,, 11 ( 5 1 ) ( 1 1 ) : p t : dp t = t dt + t dw t t, W t, r t + h, h = l p t + h - l p t : r t + h, h Π { t +, t + } h = 0 N ( h t + d, 0 h t 0 + d ) h t 0 + d,, 0, : r j = 1,,,[ hπ ] t + j, r t + j, - h 0 t + d 0 ^ = r j = 1,,,[ hπ ] t + j, r t + j, (1),, 0, 0 1 r, N, N { r 1, r,, r N }, N :, N = 1 N = > 1, 1 = r = r i = 1 i = = + r i r j r i + i = 1 i = 1 j = i +1 N = N r i = 1 i Chia Academic Joural Electroic Publishig House. All rights reserved. i = 1 j i = r i r j = + i = 1 - i j = 1 r i + i = 1 r i r j i = 1 j = i +1 r i r i + j () : = + * 76, ^ = r i = 1 i :

N { r 1, r,, r N }, N :, N = 1 N = > 1, 1 = r = r i = 1 i = = + r i r j r i + i = 1 i = 1 j = i +1 N = N r i = 1 i 1994-010 Chia Academic Joural Electroic

3 E r i - i = 1 = 4 ( K i - 1) i = 1 - i i (3) K i r i, i r i i ( Karatzas, Shreve, 1988) (3),,,,,,, (), E( r i r i + j ) < 0, (3),, r i i,, i ( ),, 31 A B, : 003 y = - k 1 ( x - x 0 ) I - x- x 0 + k ( x - x 0 ) I + x- x 0 (4) y, x, I - x - x 0 x - x 0 < 0 1, 0 ; I + x - x 0 x - x 0 0 1, 0 x 0 k 1 k,, k 1 k, 41,, ( Fractioal Itegrated Autoregressig Movig Av erage,arfima) : ARFIMA,ARFIMA ( p, d, q) <( L) (1 - L) d y t = ( L) t (5) y t ( ), t, <( L ) ( L ) L p q, d, d = 0, ARFIMA ( p, d, q) ARMA ( p, q), d = 1, ARIMA d, GPH, Geweke Porter Hudak (1983), : I ( ) = X j = 1 je j i Π( N), i, = kπn I ( ), I ( ) - d, : l ( I ( k ) ) = l si ( k Π) + ^ 1, d = - 1, Chia Academic Joural Electroic Publishig House. All rights reserved. 77

ARFIMA,ARFIMA ( p, d, q) <( L) (1 - L) d y t = ( L) t (5) y t ( ), t, <( L ) ( L ) L p q, d, d = 0, ARFIMA ( p, d, q) ARMA ( p, q), d = 1, ARIMA d, GPH, Geweke Porter Hudak (1983), : I ( ) = X

4 : 11 A B A 5510, 519, 485, B , 513, ( ) A, B B B A, B A, B, 7,, B , B A 6,,, A B, A 6,, 513 1,,, Torbe G. Aderse 30, 5,,,,, 1 ( ) 1,,,, ;,,,,,,,, Chia Academic Joural Electroic Publishig House. All rights reserved.

5 003 A ( ),,,, (),, (3), i,, 3 A ( ) 3, 1,, ( ),, ( ),, 10 17, : ^ t = 5 ^ i = 1 t - 3+ i Π5,^ t = 5 ^ i = 1 t - 3+ i Π5,,,,, ( ),,,, 3, 16, (,000001, ) 4, 1,, Chia Academic Joural Electroic Publishig House. All rights reserved.

6 : ( ),, ( ),, 10 15,,,,, ( ),,,, 4, 15, , A B 5 A 6 B, A ( ) , ,001 7 B ( ) 001,, ( ),,, B A 7 A B 7, A B , 016, ,001 3, 016, A B, (4) : y = - k 1 ( x - x 0 ) I - x- x 0 + k ( x - x 0 ) I + x- x 0 y, x, I - x - x 0 x - x 0 < 0 1, 0 ; I + x - x 0 x - x Chia Academic Joural Electroic Publishig House. All rights reserved.

7 , 0 A B, : A B, X0 K1 k R F A B , (4) A B, A R 013, B R 01167,,, k 1 k, A B, A B x 0 0,,,, R 01019, 41,, ARFIMA ARFIMA, : I ( ) = X j = 1 je j i Π( N), i, = kπn I ( ) - d, : l ( I ( k ) ) = l si ( k Π) + ^ 1, d = - 1, 3 A B Beta R d A B A B , l( I ( k ) ), (MA5), 3, R, 0 015, 3 B 018, A A B, B, ( ),,,, 5 15, Chia Academic Joural Electroic Publishig House. All rights reserved. 81

3199, (4) A B, A R 013, B R 01167,,, k 1 k, A B, A B x 0 0,,,, R 01019, 41,, ARFIMA ARFIMA, : I ( ) = X j = 1 je j i Π( N), i, = kπn I ( ) - d, : l ( I ( k ) ) =

8 : A B,,,,, A B, ;, A B, B, A,1998,, Aderse T. G. ad Bollerslev T.,1998a, Aswerig the Skeptics : Yes,Stadard Volatility Models do provide accurate Forecasts. Iteratio al Ecoomic Review 39 : Aderse T. G. ad Bollerslev T.,1998b, DMDollar Volatility : Itraday Activity Patters,Macroecoomic Aoucemets,ad LogerRu Depedecies,Joural of Fiace,Vol. 53, Aderse T. G., Bollerslev T., Diebold F. X., ad Labys P. 001a, The Distributio of Exchage Rate Volatility, Joural of the Ameri ca Statistical Associatio, Workig Paper Aderse T. G., Bollerslev T., Diebold F. X., ad Labys P. 001b, Exchage Rate Returs Stadardized by Realized Volatility are (Near ly) Gaussia, Multiatioal Fiace Joural, i press. Aderse T. G., Bollerslev T., Diebold F. X. ad Ebes H. 001, The Distributio of Realized Stock Retur Volatility, Joural of Fi acial Ecoomics, i press. Aderse T. G., Bollerslev T., Diebold F. X., ad Labys P. 001, Modelig ad Forecastig Realized Volatility. Baillie R. T., Bollerslev T. ad Mikkelse H. O. 1996, Fractioal Itegrated Geeralized Autoregressive Coditioal Heteroskedasticity, Joural of Ecoometrics 74 : Bollerslev T. 1986, Geeralized Autoregressive Coditioal Heteroskedasticity, Joural of Ecoometrics, 31, Bollerslev T. ad Mikkelse H. 1996, Modelig ad Pricig LogMemory i Stock Market Volatility, Joural of Ecoometrics, 73, 151 Chug C. F. ad Baillie R. T. 1993, Small Sample Bias i Coditioal SumofSquares Estimator of Fractioally Itegrated ARMA Models, Empirical Ecoomics 18 : Doorik J. A. ad Ooms M. 001, Computatioal Aspects of Maximum Likelihood Estimatio of Autoregressive Fractioally Itegrated Movig Average models, Ecoomic Papers 001W7ΠEcoomics Group, Nuffield College, Uiversity of Oxford Ebes H. 1999, Realized Stock Volatility, The Johs Hopkis Uiversity. Egle R. F. 198, Autoregressive Coditioal Heteroskedasticity with Estimates of the Variace for U. K. Iflatio. Ecoometrica 50 :987 Egle R. F. ad T. Bollerslev 1986, Modellig the Persistece of Coditioal Variaces, Ecoometric Reviews, 5, Egle R. F., Lilie D. M. ad Robis R. P. 1987, Estimatig Time Varyig Risk Premia i the Term Structure : The ARCHM Model. Ecoometrica 55 : Hauser M. A. 1997, Maximum Likelihood Estimators for ARFIMA Models : A MoteCarlo Study, Discussio paper, Departmet of Statis tics, Uiversity of Ecoomics ad Busiess Admiistratio, Viea, Austria. Hery O. 1998, Modellig the Asymmetry of Stock Market Volatility, Applied Fiacial Ecoomics, 8, Sowell F. 199, Maximum Likelihood Estimatio of Statioary Uivariate Fractioally Itegrated Time Series Models, Joural of Ecoomet rics, 53, ( : ) ( : ) Chia Academic Joural Electroic Publishig House. All rights reserved.

X., ad Labys P. 001a, The Distributio of Exchage Rate Volatility, Joural of the Ameri ca Statistical Associatio, Workig Paper 6961. Aderse T. G., Bollerslev T., Diebold F. X., ad Labys P. 001b, Exchage Rate Returs Stadardized by Realized Volatility are (Near ly) Gaussia, Multiatioal Fiace Joural, i press.

9 Aalysis o Character ad Highfrequecy Estimatio i Chia s Stock Market Huag Houchua & Che Liaga (Nafag Fud,Zhogsha Uiversity) This paper utilizes highfrequecy data to estimate the realized volatility i Chiese stock market. We foud that the microstructure bias of sigle stock is opposite to that of stock idex. By employig data with very highfrequecy,the realized volatility of sigle stock would be much higher,whereas that of stock idex would be much lower. Based o the realized volatilities estimated with dif feret frequecies,we develop a more accurate estimate method,which effectively balaces the microstructure error ad usual esti mate error. With the realized volatility,we ivestigate some style facts of the volatility for stock idexes,such as the leverage effect ad the log memory effect. Key Words : volatility ;leverage effect ;log memory effect JEL Classificatio : G100,C510 The Market Liquidity of Cotractig ad Operatig Right to Rural Lad : A Theoretical ad Empirical Study Qia Zhoghao ( Yagzhou Uiversity) The market liquidity of cotractig ad operatig right to rural lad (MLCORRL) depedets o the effective rural lad demad ad supply. The impact of relative factors, such as lad productio price, oproductive retur,productive cost, oproductive cost,lad price,trasactio cost ad lad scale o rural lad supply ad demad were aalyzed by decisio model i MLCORRL, The coclusios followed :lad demad exceeded the lad supply as a whole ad the market is faced the costrait of rural lad de mad,improvemet o the exteral coditio of the MLCORRL should be made to promotthe effective rural lad supply. Key Words : Cotractig ad Operatig Right to Rural Lad ;Market Liquidity JEL Classificatio :Q150,Q Chia Academic Joural Electroic Publishig House. All rights reserved.

By employig data with very highfrequecy,the realized volatility of sigle stock would be much higher,whereas that of stock idex would be much lower.

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