Intraweek and intraday trade patterns and dynamics

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Abstract

This paper investigates informed traders' order-splitting strategies on different days of the week and times of the day for a sample of stocks traded on the Australian Stock Exchange. Based on cumulative price changes, we document that informed traders tend to use medium size trades. We find that informed investors concentrate their strategic trading on Mondays and particularly during the first trading hour. In addition, informed investors also use large size trades around market opening and closing, as well as on days other than Mondays and Fridays. These results are more pronounced for the large market capitalization stocks.

Introduction

This paper investigates informed investors' trading strategies during the day and throughout the week by using limit order book data for a sample of stocks traded on the Australian Stock Exchange (ASX).1 Informed traders prefer to hide their superior information from other traders by splitting their orders. They do this for several reasons: to reduce the execution cost, to minimise the non-execution risk and to decrease the likelihood of picking-off risk (Engle et al., 2008).

Kyle (1985) presents a theoretical model that explores the strategic behaviour of informed investors in a single as well as continuous action setting. The informed investor is considered an “information monopolist” as he or she is the only agent that knows the true value of the firm. Kyle's model is significant as it not only predicts that informed investors will split their large size trades into smaller size trades in order to camouflage their transactions but also suggests that informed investors observe the condition of the order flow prior to submission as it enables them to better conceal their transactions.

Barclay and Warner (1993) is the first empirical study to explore the particular trading strategy (“stealth trading”) employed by informed investors. The authors argue that informed traders do not place large trades but instead break up their large trades into smaller trade sizes. The medium size trade is small enough to camouflage their private information and large enough to avoid high transaction costs. Chakravarty (2001) extends the literature by showing that the primary source of price movement is that of medium size trades initiated by institutional investors. Chakravarty et al. (2004) document that informed traders trade across both the stock and options markets, and that a significant amount of price discovery takes place in options markets. While Anand and Chakravarty (2007) find significant support for stealth trading in the options markets, Chakravarty et al. (2005) also document stealth trading in the Australian stock market. Their results indicate that informed investors tend to either break up their trades into small (i.e. trades of 1–499 shares) or medium size trades (i.e. trades of 500–9999 shares).2

In this paper we address the following two questions: 1) Do informed investors concentrate their trades at any specific time-of-the-day and on any specific day-of-the-week? 2) If so, do they employ different trading strategies (order-splitting) for different times of the day and days of the week? Answers to these questions will provide further insights about the way strategic investors trade. The current paper contributes to the literature by investigating the interrelation between either the intraday or inter-day stock anomalies with the stealth trading strategies performed by informed traders.

The inter-day trading patterns, otherwise known as the “Monday effect”, are well documented in the finance literature (see, among others, Cross, 1973, French, 1980, Gibbons and Hess, 1981, Rogalski, 1984; and Flannery and Protopapadakis, 1988). Studies have shown that returns and volume are lowest and bid/ask spreads are highest on Mondays across various financial products and financial markets (e.g. Keim and Stambaugh, 1984, Jaffe and Westerfield, 1985, Ball and Bowers, 1988, Finn et al., 1991).3 Foster and Viswanathan (1990) provide a theoretical model to explain this anomaly by arguing that information accumulates over the weekend, thus specialists and liquidity traders are most sensitive to order flow on Mondays. Since informed investors and discretionary liquidity traders can move their trades to the next trading day, discretionary liquidity traders have incentives to pool their trades together and are more likely to trade in the middle of the week. Foster and Viswanathan's (1993) empirical findings support this view. The authors show that discretionary liquidity traders avoid trading on Mondays and that the adverse selection cost is higher for actively traded stocks on Mondays.

Empirical research also provides evidence of intraday variations of bid/ask spreads, volume and volatility.4 Admati and Pfleiderer's (1988) theoretical model postulates that although there is no trading before market opening and after closing, discretionary liquidity traders concentrate their trades just after opening and prior to closing. McInish and Wood (1991) further dissect the intraday volume into two components (number of trades and number of shares per trade) and show that informed traders use different trade sizes across the day. McInish and Wood (1992) demonstrate that bid/ask spreads follow a U-shape pattern, indicating that the adverse selection cost is higher at the beginning and at the end of the day.5 Furthermore, when do informed investors trade and in what trade size? A recent study by Comerton-Forde et al. (2007) analyses the intraday variations in spreads, volume, volatility and proportion of informed trading. The study uses a unique data set from the Helsinki Stock Exchange (HEX) which combines trade and order (quote) data with audit data from the Finnish Central Securities Depository register. The researchers are able to precisely categorise the investors into over 29 different investor classes. Two classes are categorised as informed investors, namely “Other Financial Institutions” and “Insurance Institutions”. Moreover, the study documents that both informed and liquidity traders concentrate their trades at the open and close of the trading session, results which are consistent with theories in the literature that are based on strategic behaviour models (Kyle, 1985, Admati and Pfleiderer, 1988, Foster and Viswanathan, 1990, Foster and Viswanathan, 1993).

In this study we use both transaction and limit order book data from the ASX over a three-month period between 1 October 2001 and 31 January 2002. We use all stocks that experienced an increase of at least 5% in value above the market index. During our sample period the main market index increased approximated by 11.5%. We argue that if informed trading activities are taking place, these are likely to occur during a period of extreme market demand. The main findings of this study are summarized as follows. First, we document a stealth trading in the ASX. Second, we observe an inverted U-shaped pattern of investors' inter-day trading activities. In order to minimise their transaction costs, informed traders are unlikely to transact at the start of the week and often postpone their transactions to other days of the week (other than Mondays and Tuesdays). Third, the inter-day (intraday) distribution of cumulative price changes reveals that informed trading is concentrated on Mondays and during the first trading hour of the day. Fourth, a closer examination of the trade sizes across the week reveals that there is some evidence of order-splitting (stealth trading), especially on Mondays. Furthermore, the results also provide weak evidence for informed investors using different trading strategies across the week. These investors use larger size trades when liquidity is available and medium size trades on Mondays in order to camouflage their transactions. Next, there is a high concentration of trading activity within the first trading hour of the day. The distribution of the cumulative price changes reveals that there is more order-splitting during the first hour of trading than at any other time. It appears also that informed investors spread their trades in the first two trading hours. Finally, we document that informed investors use large size trades between 14:00 and 15:00. This finding provides evidence that informed investors use a dynamic trading strategy across the day, as they will use medium size trades when the information asymmetry cost is high and use large size trades when the information asymmetry cost is low.

The remainder of the paper is organised as follows. Section 2 provides details about the data, sample selection, methodology and measurements employed in this study. Section 3 discusses the results and their implications. In Section 4, the sensitivity analysis of the results is summarized, and finally, Section 5 concludes and gives directions for future research.

Section snippets

Data and sample selection

The Security Industry Research Centre of Asia-Pacific (SIRCA) provided us with two data sets containing: 1) trade-by-trade information with the date of the trade, the time to the nearest hundredth of a second, stock code, transacted price, volume, value, buy/sell trade indicator, and unique transaction indicator and 2) the limit order book data which contain records of the following: the order type (order submission, revision, cancellation and execution), the date and time, stock code, order

Descriptive statistics

Table 1 presents basic statistics on the average percentage of price change, average trade sizes, average daily volumes, investor types, and order imbalance (OI) of buy- and sell-initiated trades. Panel A reports the number of stocks and mean, minimum and maximum price movement in each of the periods. Panel B compares the average trade size, number of trades and daily volume across the sample. The average trade size is close to 4700 shares and the daily volume measured by the number of

Sensitivity analysis

Trade sizes have been classified according to previous studies (Barclay and Warner, 1993, Chakravarty, 2001). We recognize that this classification is arbitrary; however, there is no prior theoretical framework to suggest a more appropriate classification. To improve the robustness of this study, we provide an alternative measure of trade size by following Bessembinder and Kaufman's (1997) dollar value trade size classification, where small trades are defined as trades between $1 and $9999,

Conclusion

The present study examines the impact of the time-of-the-day and day-of-the-week on the patterns of informed investors' trading. We found an inverted U-shaped pattern of investors' inter-day trading activities. The distribution of trading volume and number of transactions varies across the week with the lowest volume/number of transactions on Mondays and the highest on Wednesdays. These results are consistent with Foster and Viswanathan (1990). This difference in trading volume reflects: 1) the

Acknowledgements

We thank the participants of the Modelling and Managing Ultra High Frequency Data International Conference, Perth 2008; University of Sydney Microstructure Conference, Sydney 2008 and; in particular, Dave Allen, an anonymous referee, Carole Comerton-Forde (The Guest Editor), Ghon Rhee (The Editor) and Avanidhar (Subra) Subrahmanyam for their helpful comments and constructive suggestions on earlier versions of this paper. We are grateful to the Securities Industry Research Centre of Asia-Pacific

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