[雙語(yǔ)翻譯]經(jīng)濟(jì)學(xué)外文翻譯--資本流動(dòng)性和市場(chǎng)效率基于納斯達(dá)克上市公司的分析（英文）

1、Liquidity and market efficiency: Analysis of NASDAQ firmsDennis Y. Chung?, Karel HrazdilFaculty of Business Administration, Simon Fraser University, Burnaby, BC, V5A 1S6, Canadaa r t i c l e i n f o a b s t r a c tArticl

2、e history:Received 13 May 2010Accepted 3 June 2010Available online 17 September 2010We analyze all NASDAQ firms with respect to their short-horizon returnpredictability, which Chordia et al. (2008) formulate as an invers

3、eindicator of market efficiency. Our results confirm that increasedliquidity enhances market efficiency, and show that this effect isamplified during periods with new information. After controlling forliquidity and infor

4、mation effects, we find that NASDAQ firms experiencean improvement in market efficiency only from the sixteenth to thedecimal tick size regimes. We further demonstrate that inferences ofmarket efficiency are not uniform

5、across the different portfolios formedon the basis of trading frequency, volume and market capitalization.© 2010 Elsevier Inc. All rights reserved.JEL classification:G10G14Keywords:LiquidityReturn predictabilityMark

6、et efficiencyNASDAQ1. IntroductionChordia, Roll, and Subrahmanyam (2008, hereafter referred to as CRS) examine market efficiency acrossthree tick size regimes and document a substantial decline in short-horizon return pr

7、edictability for asample of New York Stock Exchange (NYSE) companies. The argument is that the short-horizonpredictability of stock returns from past order flows is an inverse indicator of market efficiency and CRSprovid

8、e compelling evidence that the market is becoming more efficient as the tick size decreases.1 Oneimportant implication of the CRS study is that their approach provides a feasible basis for estimating thedegree of informa

9、tional efficiency in a market. Research utilizing this approach in connection with NYSEfirms is also beginning to appear in the literature (e.g., Aktas, de Bodt, Visaltanachotifax: +1 778 782 4920.E-mail addresses: dych

10、ung@sfu.ca (D.Y. Chung), karel_hrazdil@sfu.ca (K. Hrazdil). 1 CRS analyze a period of three tick size regimes between 1993 and 2002 in which the NYSE changed its minimum tick size from $1/8 to $1/16 on June 24, 1997, and

11、 further to $0.01 on January 29, 2001.1044-0283/$ – see front matter © 2010 Elsevier Inc. All rights reserved.doi:10.1016/j.gfj.2010.09.004Contents lists available at ScienceDirectGlobal Finance Journaljournal homep

12、age: www.elsevier.com/locate/gfjefficiency. Liquidity, in this case, is positively associated with market efficiency. Second, if market makersfail to utilize the information in order flows and eliminate return predictabi

13、lity, then other marketparticipants have incentives to gather new information about order flows and trade on such information.While the increased adverse selection faced by market makers lowers liquidity, market is more

14、efficient asmore information is incorporated in prices. Liquidity, in this case, is negatively associated with marketefficiency.Using short-horizon returns and lagged order imbalance measures on 193 NYSE firms (the large

15、st 500firms on the NYSE with daily trading throughout the sample period), CRS show that return predictabilitydropped substantially and market efficiency increased over the three tick size regimes of improvedliquidity.2 T

16、he positive association between liquidity and market efficiency supports their first hypothesisand conclusion that higher liquidity facilitates arbitrage trading which reduces return predictability andenhances market eff

17、iciency. CRS perform additional analysis using return variance ratios and returnautocorrelations and provide evidence suggesting that new information is more effectively incorporatedinto prices during more liquid regimes

18、. CRS conclude that “increases in liquidity facilitate efficiency viatwo distinct channels. First, return predictability from order flows is diminished during periods of highliquidity because arbitrageurs are better able

19、 to assist specialists in absorbing order flows during suchperiods. Second, a reduction in the minimum price change allows for the collection of more informationthat, in turn, increases informational efficiency by allowi

20、ng prices to reflect more information aboutfundamentals” (p. 266).With new information introduced to the market, it is likely that the dynamic in the liquidity and marketefficiency relation will also change. We address t

21、his issue empirically in our study. We identify periods ofincreased adverse selection as indications of new information in the market and present evidence that highadverse selection interacts positively with liquidity to

22、 produce significantly stronger positive effect onmarket efficiency. We further find that improved liquidity and new information both contribute to enhancemarket efficiency, which strengthens conclusions by CRS and valid

23、ates the usefulness of returnpredictability as an indicator of market efficiency for future research designs.CRS acknowledge the issue of infrequent trading when they decide on the appropriate length of theintraday inter

24、val over which returns and order flows are measured.3 Furthermore, CRS circumvent theinfrequent trading issue by excluding medium and small stocks from their study and requiring all firms intheir final sample to have tra

25、ded every day throughout their sample period. For our study, we include allNASDAQ firms and we examine how trading frequency impacts the relation between liquidity and marketefficiency and whether order flow information

26、is useful in assessing return predictability when order flowand trading information is available from one five-minute interval to the next.2.2. Institutional detailsThe differences in the exchange characteristics, such a

27、s trading rules, treatment of limit orders, oropening price setting mechanisms arguably play a role in the extent to which liquidity is related to marketefficiency.4 For instance, while both NYSE and AMEX are order drive

28、n auction markets (with monopolisticand specialist dealers), NASDAQ is a more competitive, multiple dealership market. Apart from their ownaccounts, specialists facilitate trading through limit orders that provide a larg

29、e component of liquidity onthe NYSE/AMEX, whereas on NASDAQ, with no central limit order book, dealers continuously post firm bidand ask quotes on an electronic screen. Further, following price relevant news releases, li

30、mit prices onNYSE can temporarily deviate from equilibrium levels due to the “uptick rule” that prevents arbitrageursfrom short selling the security on a price down tick or a zero tick following a down tick (e.g. Alexand

31、er however, CRS consider only the 10 largest NASDAQ companies in this part of their analysis. 3 CRS use the five-minute intervals for two reasons: “First, though shorter intervals are technically possible, non-trading be

32、comesan issue. Second, though longer intervals are feasible, short-lived market inefficiencies would probably be less conspicuous oversuch intervals, since a predictive relation between order imbalances and future return

33、s is unlikely to last very long. Five minutesseems like a good compromise” (p. 252). 4 For a thorough analysis of various institutional features, see Masulis and Shivakumar (2002).264 D.Y. Chung, K. Hrazdil / Global Fina