: 3 :, 5,,,,: ;,; ;,,,, : Black (86),,,,,, Fama (7,91),, ;,,,, De Long (9) Shleifer Vishny (97) Shleifer (),,,,, (limited arbitrage),,,,, (Bloomfiled et al,8),( ),,,,,, 3,,:56,:tdsu @jnu. edu. cn,, (75765) (4JDX791) (7JDTDXM795) (4S2D3) 82
8 9,,,,, :,De Long (91), Huang Stoll (96) Berkman Eleswarapu (98),, 5,,,, ;, Stoll (),,, ;,,,, yle (85),,,,,,, ;,,, ;,,, Glosten Milgrom(85),,,,, Admati Pfleiderer (88) yle (85),, ;,,,,, ;,,,, Holden Subrahmanyam(92) Foster Viswanathan (93) Wang(98) Back () ( ) (Bertrand Cournot ) ( ),:; ; ;;, Easley (2) Gur Stanzl (4) Wang (5), (),,,,,,, 83
:, Chan Lakonishok (93) Lehmann Modest (94) Biais (95) NYSE,,, Easley (96),,NYSE, Berkman Eleswarapu (98),, 93,,,94 72 %, Greene Smart (99) (investment dartboard column),,,,, Bessembinder (3),NYSE NASDAQ 1 1 29 4 9 (decimalization),, Chakravarty (4) NYSE CBOT( ) 6,, Lei Wu (5) Easley (96),, (momentum),,,, 31 Admati (85),,,, yle (89) yle (85),,,,,, Palomino (96),,,,, Stoll (89),,,,, Madhavan (92),, Handa (3),,,, De Long (91),,,,, Campbell yle (93), 84
8 9 Vayanos(1),,,,,,, Chakraborty Yilmaz (4) Glosten Milgrom(85),,,,, Mendelson Tunca (4),,, 41 Lee (93),NYSE,,,,Damodaran Liu (93),NYSE 54 (REIT) eim Madhavan (96) 85 92 NYSE AMEX NASDAQ 5625,,, % 8 % Gemmill Thomas(2) 24,24 8 %,,24, Brown(99) ( ),, Lee (2),,,,,,,, Antweiler Frank (4) ( support vector machine algorithm), 98 Yahoo 45 NYSE,, Chordia Subrahmanyam (4) 93 98 NYSE2TAQ,NYSE, ( ) ( ),,,,,,,, ;,,,,,,, 85
: De Long (9),,,,,,, De Long (9),,, CSMAR 562, ST PT 3 ST 75,4 5,, -, Y j, l : Y j, l =, P O j P O j - P C j, l ( P O j + P C j, l )Π2 2 + M O j - M C j, l ( M O j + M C j, l )Π2 2 + BM O j - BM C j, l ( BM O j + BM C j, l )Π2 2 + DA O j - DA C j, l ( DA O j + DA C j, l )Π2 P C j, l j ( j = 1,,) l ( l = 1,,486) 1 28, M O j M C j, l j l, BM O j BM C j, l j l - ( ), DA O j (1) DA C j, l j l ( ) j, Y j, l 2 3, j,, CSMAR TAQ2CS(3 ) 2 7 1 3 6,, ( ) (),: r O j, t r C j, t = 1 L = (ln P O, C j, t l = 1 MC j, l - ln P O, O j, t ) (2) L M C j, l (ln P C, C j, l, t l = 1 - ln P C, O j, l, t ) (3), r O j, t r C j, t j t ( ), j = 1,, t = 1,,36 (6, ),(basis point,1 ), P O, C j, t P O, O j, t j, P C, C j, l, t P C, O j, l, t l ( l = 1,,L,L 3) (3),,,,De Long (9) Berkman Eleswarapu (98),, : r O j, t = j + j r C j, t + j r C j, t +1 + j, t (4),(4) j ( ^ j + ^ j r C j, t + ^ j r C j, t + 1 ) ( ^ j, t ), 2 j l, j l, j l, j 86
8 9,( ), 1 NOS j, t = ^ 2 j, t Jones (94),:, P O, H j, t P O,L j, t V j, t = 2, H PO j, t - P O,L P O, H j, t + P O,L j, t j, t j 2 (),,,,,,1,, (, 5),(relative quoted half spread), : QS j, t = ga j, t - gb j, t, H 2 j, t = ga j, t + gb j, t H j, t 2, ga j, t gb j, t j, H j, t, j t 2 (,4), : TO j, t (5) (6) (7) = VOL j, t TS j, t (8),VOL j, t j, TS j, t (A ) 2,,,, Stoll (),, 2 IA j, t = H j, t - H j, t - 1 H j, t (9),, ga j, t gb j, t,qs j, t Stoll (),(relative effective half2spread,h j, t H j, t ), 87
:,,,Stoll (),(realized half spread) : RS j, t = PO, C j, t - P O, C j, t - 1 H j, t (), () 1, 367,6 %, ( %, 15 %, 75 %) ; 241,, ; 9 %, ; ;,( %), ;,, ( 1 % ) ( 5 %), 1 V QS TO IA RS NS 46. 61 1. 38. 2582 333. 351 33. 9 333. 458 333 -. 55 333 V. 38 25. 61. 4. 72 333. 9 -. 384 33 ( ) QS 36. 27 48. 55. 333. 63 333 -. 38 3 ( ) TO. 29. 6. 274 -. 6 IA 24.. 85 -. 5 ( ) RS 1. 69 2. 37 : ( %), (1 ) 333 33 3 t % 5 % % 1 % 5 % % 363 6 293, 1,, : 1 :45,2 :,, V ; ;, t = 1 ( ),P O j,, C RS j,1 88
8 9,, U, 1 ;, ; ;,, 31 VAR,, (VAR),, 1 : 5, 2 7 1 3 6 6, VAR : NS t L t + 1 k NS t - k + 2 k L t - k + 3 k IA t - k + 4 k V t - k + = = + 1 k NS t - k + 2 k L t - k + 3 k IA t - k + 4 k V t - k + IA t = < + V t RS t = < 1 k NS t - k + < 2 k L t - k + < 3 k IA t - k + < 4 k V t - k + + 1 k NS t - k + 2 k L t - k + 3 k IA t - k + 4 k V t - k + = + 1 k NS t - k + 2 k L t - k + 3 k IA t - k + 4 k V t - k + 5 k RS t - k + 1 t 5 k RS t - k + 2 t < 5 k RS t - k + 3 t 5 k RS t - k + 4 t 5 k RS t - k + 5 t,l t QS t TO t ;,Akaike (AIC) Schwartz (BSIC),GAUSS BHHH VAR,, = 2,AIC 2 3 VAR, t % 5 % %, Granger 1 % 5 % % 2, Granger () (3) U,(2) (4) L, (4) (4),,, L (2) (4) U, 89
: 2 3 :,, 5 %( 1 %),,, 27 25, 8 %, (2 3 RS RS ),^ 27 24, 2 %,, Granger 5 % = = (2 NS QS 3 NS TO ),,,,,, Admati Pfleiderer (88),,,,,,,,^ 29 27, %,, Granger 5 % = = (2 3 NS V ),,De Long (91) Campbell yle (93),,,^, 9 %,, Granger 5 % = = (2 3 NS RS ),,,,^< 6 4 %, Granger 4 3 % < = < = (2 3 NS IA ), Chakraborty Yilmaz (4) Mendelson Tunca (4),,, (Admati, 85) ( yle, 89),, ^< 27 24, %,,Granger % 31 = = < = < = (2 IA TS TS IA ),,, t - 1, t, t + 1, t + 2,, Back () Handa (3),,,,, 9
8 9 2 VAR NS QS IA V RS NS () () ^. 2429 (,,) ^. 37 24 (2,3,1) 8 ^. 48 27 (6,9,3) 5 ^ -. 825 (1,2,1) (,5,1) ^<. 863 (,,3) ^< -. 251 (,3,1) ^. 682 29 (,6,1) 3 ^. 91 (1,5,2) ^ -. 3 (1,2,2) (4,5,1) ^ -. 286 QS Granger [] () () ^. 774 (1,3,2) [,, ] [,2, ] [1,1,2 ] [,2, ] [7,4,2 ] ^ -. 285 ^. 256 (31,1,) ^. 94 (1,4,2) (,3,1) ^<. 82 24 (7,3,4) 8 (,1,) ^<. 437 (,2,5) (,3,1) ^ -. (2,1,) ^. 71 (,1,) ^ -. 66 (,1,1) ^. 82 9 23 (,5,) IA V Granger [] () () Granger [] () (). (1,,4) (,3,2) 2. 7 (2,1,1) (,1,) [1,5, ] [,, ] [,4, ] [3,1, ] [,4, ]. 6 (,3,1) 4. 63 27 (9,2,5) 5-1. 74 (1,,3) (,2,2) ^< 31. 39 (3,2,) ^<. 474 (1,,3) 2. 7433 (,,4) -. 283 (,1,3) (,,3). 79 (1,2,1) (1,1,) [2,2, ] [,2,1 ] [,, ] [1,5, ] [2,1,3 ] ^< 41 ^< 42 -. 6642-1. 93 -. 656-1. 87. 733 (1,3,) (,1,3) (,,5) (,1,). 24 (28,4,) -. 62 (,1,1) (,1,4) -. 86 -. 63. 38 (1,,1) (3,,1) (,2,2) (2,3,1) (1,1,4) (1,,3) RS Granger [] () () - 5. 6344 8 24 (2,,3) [2,3,1 ] [,4, ] [,2, ] [,, ] [3,3, ] 2. 259 (,4,) (,1,3) - 2. 237 (2,1,1) (1,3,1). 8646 (,3,1) (1,2,1) ^< 51 ^< 52 -. 483 -. 27. (2,,2) (1,,) (2,1,1) -. 94 -. 279 -. 74 (1,,) (,,3) 5 27 (5,6,1) (2,1,2) (1,,3) Granger [] [2,2,1 ] [4,1,1 ] [3,, ] [3,,1 ] [,1,1 ] :t % 5 % %, Granger 1 % 5 % % 91
: 3 VAR NS QS IA V RS NS () () ^. 3463 (,,) ^. 9 28 (3,2,1) 4 ^ 1. 36 24 (,6,) 8 ^ -. 91 (1,,5) (2,2,) ^< -. 236 ^< -. 82 (,1,1) ^. 52 27 (,4,3) 5 (1,,) ^. 968 (5,,1) (2,2,) ^ -. 96 (1,1,1) (5,2,2) ^. 88 (1,2,) (,1,1) QS Granger [] () () ^. 16 (1,,2) [,, ] [,2, ] [1,2, ] [,, ] [7,3,1 ] ^ -. 481 (,1,1) ^. 3528 (3,2,) ^. 63 (3,,1) (1,,2) ^<. 69 (1,1,) (2,,) ^<. (,,3) (1,1,) ^ - 2. 2492 (,4,) ^. 8533 (1,2,) ^ - 1. 352 (1,2,3) ^. 36 (,3,1) (,1,1) IA V Granger [] () () Granger [] () (). 5 (1,1,3) 3. 6424 (2,,3) [1,2,1 ] [,, ] [3,1,1 ] [2,3, ] [3,1,1 ]. 463 (1,,1) - 1. 7691 7 25 (,4,) -. 4925 (,1,2) ^< 31. 2688 (31,1,) ^<. 591 (2,2,1) 5. 55 (1,3,1) (,1,) - 4. 973 (1,,2) 2. 86 (2,,3) (1,1,1) [1,3, ] [1,3, ] [,, ] [4,,1 ] [3,2,1 ] - 2. 7639 (1,3,). 88 (,3,1) (1,,). 437 (,1,2) ^< 41-4. 62 8 24 ^< 42 2. 58 (1,2,). 23 (,,) - 1. 699 7 25 (,4,1) -. 386-3. 66 1. 749 (,4,) 9 (1,,1) 23 (2,2,) (1,2,) RS Granger [] () () - 4. 36 (2,2,) [2,3, ] [3,2, ] [2,2, ] [,, ] [3,1,1 ] 1. 9623 (2,1,) (1,1,1) - 1. 9 (2,1,1). 75 (1,,3) (,1,2) ^< 51. 96 (2,,3) (1,1,) ^< 52 -. 4795-2. 33 1. 3725 (,3,1) 9 (,1,) 23 (3,,1) (1,2,1) -. 4 -. 46 7 (,1,) 25 (3,2,3) (1,3,) Granger [] [3,1,1 ] [2,3, ] [3,1,2 ] [3,, ] [4,3,2 ] :t % 5 % %, Granger 1 % 5 % % 92
8 9,, QS TO IA V RS NS Granger 4 6,,Granger (2 3 NS ),,,,, ; ;, ;,,,,,,,,,,, (),,,,,,,,,,,,,,VAR Granger,,,,,,,,,,,,,,,,,,,,,,,,,, Granger, ( ), 93
:,4 :, 1,4 :, : 3,2 :, 1,4 :, 2,5 : :,3,4 ::, 2,3 :, 5 Admati, A. and P. Pfleiderer, 88, A Theory of Intraday Patterns : Volume and Price Variability, Review of Financial Studies 1, 3 4. Antweiler, W. and M. Z. Frank, 4, Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards, Journal of Finance 59, 59 94. Back,., H. Cao, and G. Willard,, Imperfect Competition Among Informed Traders, Journal of Finance 55, 25. Berkman, H. and V. R. Eleswarapu, V. R., 98, Short Term Traders and Liquidity : A Test Using Bombay Stock Exchange Data, Journal of Financial Economics 47, 339 355. Bessembinder, H., 3, Trade Execution Costs and Market Quality After Decimalization, Journal of Financial and Quantitative Analysis 38 : 747 777. Biais, B., P. Hillion and C. Spatt, 95, An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse, Journal of Finance 5, 55 89. Black, F., 86, Noise, Journal of Finance 41, 529 543. Bloomfield, R., M. OπHara and G. Saar, 8, How Noise Trading Affects the Market : An Experimental Analysis, forthcoming in Review of Financial Studies. Brown, G. W., 99, Volatility, Sentiment, and Noise Traders, Financial Analysts Journal 55, 82 9. Campbell, J. Y., and A. S. yle, 93, Smart Money, Noise Trading and Stock Price Behavior, Review of Economic Studies 6, 1 34. Chakraborty A. and B. Yilmaz, 4, Informed Manipulation, Journal of Economic Theory 1, 2 2. Chakravarty, S., 1, Stealth2Trading : Which Traderπs Trades Move Stock Prices?, Journal of Financial Economics 61, 289 37. Chakravarty, S., H. Gulen and S. Mayhew, 4, Informed Trading in Stock and Option Markets, Journal of Finance 59, 35 57. Chan, L. and J. Lakonishok, 93, Institutional Trades and Intraday Stock Price Behavior, Journal of Financial Economics 33. Chordia T. and A. Subrahmanyam, 4, Order Imbalance and Individual Stock Returns, Journal of Financial Economics 72, 485 5. Damodaran, A. and C. Liu, 93, Insider Trading as A Signal of Private Information, Review of Financial Studies 6, 79 1. De Long, J. B., A. Shleifer, L. H. Summers and R. J. Waldmann, 9, Noise Trader Risk in Financial Markets, Journal of Political Economy 98, 73 738. De Long, J. B., A. Shleifer, L. H. Summers and R. J. Waldmann, 91, The Survival of Noise Traders in Financial Markets, Journal of Business 64, 1. Easley, D., N. M. iefer, M. OπHara and J. B. Paperman, 96, Liquidity, Information, and Infrequently Traded Stocks, Journal of Finance 51, 5 36. Easley, D., S. Hvidkjaer and M. OπHara, 2, Is Information Risk A Determinant of Asset Returns, Journal of Finance 57. Fama, E. F., 7, Efficient Capital Markets : A Review of Theory and Empirical Work, Journal of Finance 25, 383 4. Fama, E. F., 91, Efficient Capital Markets : II, Journal of Finance 46, 75. Foster, F. D. and S. Viswanathan, 93, The Effect of Public Information and Competition on Trading Volume and Price Volatility, Review of Financial Studies 6, 23 56. Gemmill, G. and D. C. Thomas, 2, Noise Trading, Costly Arbitrage, and Asset Prices : Evidence from Closed2end Funds, Journal of Finance 58, 2571 2594. Glosten, L. R. and P. R. Milgrom, 85, Bid, Ask and Transaction Prices in A Specialist Market with Heterogeneously Informed Traders, Journal of Financial Economics, 71. Greene J. and S. Smart, 99, Liquidity Provision and Noise Trading : Evidence from the Investment Dart Board Column, Journal of Finance 55, 85 99. Gur H. and W. Stanzl, 4, Price Manipulation and Quasi2Arbitrage, Econometrica 72, 47 75. Handa, P., R. Schwartz and A. Tiwari, 3, Quote Setting and Price Formation in An Order Driven Market, Journal of Financial 94
8 9 Markets 6, 461 489. Holden, C. W. and A. Subrahmanyam, 92, Long2Lived Private Information and Imperfect Competition, Journal of Finance. 47. Huang and H. R. Stoll, 96, Dealer versus Auction Markets : A Paired Comparison of Execution Costs on NASDAQ and the NYSE, Journal of Financial Economics 41, 3 357. Jones, C. M., G. aul and M. L. Lipson, 94, Information, Trading, and Volatility, Journal of Financial Economics. 36, 7 4. eim, D. and A. Madhavan, 96, The Upstairs Market for Large2Block Transactions : Analysis and Measurement of Price Effects, Review of Financial Studies 9, 1 36. yle, A. S., 85, Continuous Auctions and Insider Trading, Econometrica 53, 36. yle, A. S., 89, Informed Speculation with Imperfect Competition, Review of Economic Studies 56, 3 356. Lee, C., B. Mucklow, and M. J. Ready, 93, Spreads, Depths, and the Impact of Earnings Information : An Intraday Analysis, Review of Financial Studies 6, 345 374. Lee, C. B. and M. J. Ready, 91, Inferring Trade Direction from Intraday Data, Journal of Finance 46, 733 747. Lee, W. Y., C. X. Jiang and D. C. Indro, 2, Stock Market Volatility, Excess Returns, and the Role of Investor Sentiment, Journal of Banking and Finance 26, 77 99. Lehmann, B. R. and D. M. Modest, 94, Trading and Liquidity on the Tokyo Stock Exchange : A Birdπs Eye View, Journal of Finance 49, 951 984. Lei, Q. and G. Wu, 5, Time2varying Informed and Uninformed Trading Activities, Journal of Financial Markets 8, 3 1. Madhavan, A., 92, Trading Mechanisms in Securities Markets, Journal of Finance 47, 67 641. Mendelson, H. and T. I. Tunca, 4, Strategic Trading, Liquidity, and Information Acquisition, Review of Financial Studies. Palomino, F., 96, Noise Trading in Small Markets, Journal of Finance 51, 37 5. Shleifer, A.,, Inefficient Markets : An Introduction to Behavior Finance. New York : Oxford University Press. Shleifer, A. and R. Vishny, 97, The Limits of Arbitrage, Journal of Finance 52, 35 55. Stoll, H. R., 89, Inferring the Components of the Bid2Ask Spread : Theory and Empirical Tests, Journal of Finance 44, 1 4. Stoll, H. R.,, Friction, Journal of Finance 55, 79. Vayanos, D., 1, Strategic Trading in A Dynamic Noisy Market, Journal of Finance 56, 1 1. Wang, F. A., 98, Strategic Trading, Asymmetric Information and Heterogeneous Prior Beliefs, Journal of Financial Markets 1. Wang, F. A., 5, Trading on Noise as If It Were Information : Price, Liquidity, Volume and Profit, Rice University Working Paper. Noise Trading and Market Quality in Chinese Stock Markets Su Dongwei (College of Economics and Institute of Research in Finance, Jinan University) Abstract :Whether and to what extent noise trading and market quality affect each other has been an active research topic in finance during the past several decades. For the first time, this paper provides time2series estimates of noise trading in the emerging Chinese stock markets by regressing high2frequency returns of Shanghai 5 index companies on a control sample composed of industry, size, leverage and book2to2market matched firms. The paper finds that private information is persistent and highly correlated ; noise trading enhances stock2market turnover, but increases trade execution costs and price volatility at the same time ; noise trading and information asymmetry are not correlated, although information asymmetry can increase trade execution costs substantially ; noise trading reduces realized spread, and as a result, market is not price efficient. Based on the aforementioned empirical findings, the paper proposes that to enhance market quality, Chinese government must deepen market microstructure reform, promote value investment strategies, improve information disclosure practices and strengthen trade monitoring. ey Words : Noise Trading ; Market Quality ; Information Asymmetry ; Market Efficiency ; Market Microstructure JEL Classification : G, G, C (: ) (: ) 95