دانلود مقاله ISI انگلیسی شماره 12653
عنوان فارسی مقاله

شواهد تجربی در تکامل نقدینگی : انتخاب بازار در برابر بازارهای سفارش محدود بوسیله معامله گران آگاه و ناآگاه

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
12653 2005 21 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
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عنوان انگلیسی
Empirical evidence on the evolution of liquidity : Choice of market versus limit orders by informed and uninformed traders
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Financial Markets, Volume 8, Issue 3, August 2005, Pages 288–308

کلمات کلیدی
سفارشات محدود پنهان - رفتار معامله گر - کیفیت بازار - بازارهای سفارش محدود الکترونیکی -
پیش نمایش مقاله
پیش نمایش مقاله شواهد تجربی در تکامل نقدینگی : انتخاب بازار در برابر بازارهای سفارش محدود بوسیله معامله گران آگاه و ناآگاه

چکیده انگلیسی

We empirically investigate the evolution of liquidity, as well as the changing strategies of informed traders, over the course of the trading day. In particular, we empirically examine the relative use of market versus limit orders by informed and liquidity traders early versus later in the trading day using detailed order and audit trail data from the NYSE. Our study complements experimental research that shows that informed traders tend to take liquidity earlier in the trading day while acting as liquidity suppliers later in the day. We find that informed (i.e., institutional) traders actually use market orders more often in the first half of the day than the second. We also find support for informed traders’ use of limit orders. Limit orders placed by informed traders perform better than those placed by uninformed (i.e., individual) traders. Our findings serve to underscore the importance of developing new theoretical models to more accurately reflect the changing and complex trading milieu.

مقدمه انگلیسی

How do informed traders behave with regard to the choice of their strategies over the course of the trading day? How do the uninformed liquidity demanding traders respond with their own strategy choices over the same period? The answers to such questions hark back to the fundamental questions related to the source and availability of liquidity, which is a crucial determinant of the success of any modern exchange. In recent years, both the regional stock exchanges and electronic markets such as ECNs have emerged as viable trading alternatives for investors. These alternative trading systems have transformed the use of limit orders, and made the role of public limit orders as suppliers of liquidity particularly significant. Given this increased prominence of limit orders in today's environment, it behooves us to understand the evolution of informed trading, especially through traders’ choice of market and limit orders, over the course of the trading day. Unfortunately, this is easier said than done. Informed traders are not observable since they take pains to disguise themselves and their trading motives, and it is left to the creative resources of empirical researchers to come up with reasonable proxies of what comprises informed (and uninformed) trades. Our research builds on the important assumption that institutions are informed traders while individuals are uninformed.1 Additionally, most publicly available intraday transactional databases do not provide details pertaining to orders behind each transaction, let alone on the counterparties to the trade, or a view of when limit orders are submitted, and the market conditions prevailing at the time of order submission. There is, however, one publicly available database which allows us to investigate the above questions. This is a well used (and well documented) audit trail of all orders and their execution details, over a well represented sample of NYSE stocks over a three month period, known as TORQ. Using this data, we find that informed initiating trades (through market orders and marketable limit orders)2 account for a higher cumulative price change in the first half of the day than the second. Thus, informed traders use market orders early on in the trading session. We also study the performance of institutional and individual limit orders after order submission and find that institutional limit orders perform better than individual limit orders. This result holds even after controlling for order and stock specific characteristics, indicating the use of information in placing limit orders and thereby demonstrating the role of limit orders in informed trading. While the extant theoretical literature provides some guidance on the question of the evolution of liquidity over the trading period (see, for example, Angel (1994), Chakravarty and Holden (1995), Harris (1998), Parlour (1998), and Kaniel and Liu (2003)), these models are stylized (i.e., restrictive) enough to make it impossible to find in them the answers to the questions we ask above. So, absent a clear direction from the existing theoretical models, it is clear that any answer on the issue of evolution of trading strategies vis-à-vis the relative usage of market and limit orders by both the informed and the uninformed traders has to come from the data itself. Bloomfield et al. (2005) (hereafter BOS) tackle this problem by experimentally modeling an electronic market to provide insight into the evolution of liquidity. BOS's experimental electronic market includes informed and large and small liquidity traders trading via market and limit orders in a continuous time setting. The emergent intuition from their study is that informed traders take liquidity earlier in the trading day with market orders so as to profit from their private information. In so doing, they push prices closer to their true values and then use their knowledge of the true price to act as dealers by switching to submitting limit orders and earning the bid-ask spread later in the trading day. Thus, toward the end of the trading period, informed traders, on average, trade more often with limit orders than do liquidity traders. The uninformed or liquidity traders tend to use limit orders early on but as the end of the trading day approaches they switch to market orders in order to meet their targets. Counter to these predictions, however, is the prevailing intuition from the theoretical literature that informed traders are much more likely to be liquidity demanders than liquidity suppliers. Angel (1994) and Harris (1998) allow for the use of limit orders by informed traders, but argue that they are more likely to use market orders. Harris (1998) predicts that informed traders are more likely to use market orders if they believe their information to be short lived. Furthermore, as trading deadlines approach, the likelihood of market order use by informed traders increases. These studies set up our alternative hypothesis that limit orders will be used sparingly (or not at all) by informed traders.3 Our study contributes to this literature by providing empirical evidence on the market versus limit order choice of informed traders. In focusing on the evolution of trading strategies of informed traders over a trading day, we also complement the experimental analysis of BOS. Empirical studies in the area have focused on various dimensions of order choice. Lee et al. (2004), for example, find that different trader types on the Taiwan Stock Exchange act as de facto liquidity suppliers while also trading based on information. Their results suggest the changing order choice of individuals and institutional investors that we study in this paper. Harris and Hasbrouck (1996) study all limit orders placed through NYSE's SuperDOT system and find that limit orders placed at or better than the prevailing quote outperform market orders. Griffiths et al. (2000) also find that order aggressiveness plays an important role in the order's performance. Biais et al. (1995) examine the role of the limit order book in order choice on the Paris Bourse. Chung et al. (1999) examine the role of the limit order traders in setting the bid-ask spread on the NYSE. They find (p. 257) that “the majority of bid-ask quotes reflect the interest of limit-order traders.”4 The plan for the remainder of the paper is as follows. In the next section we describe the data; Section 3 presents the methodology and the results. Section 4 concludes.

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