Stealth Trading Research Articles

Informed trading and cryptocurrencies. New evidence using tick-by-tick data

Do trade size preferences exist in cryptocurrencies? Using high-frequency tick-by-tick data of cryptocurrencies, we examine what trade sizes contribute to daily cumulative price changes, viz. small, medium, and large. We employ robust estimations and document the presence of informed trading in the cryptocurrency asset class, and this is specifically translated via medium and small trades. We provide evidence to support the presence of stealth trading in cryptocurrencies. Our results contradict the prevailing view that informed trades in the cryptocurrency market occur via large trades.

Foreign investors and stealth trading: An examination of price movements in developing markets

We investigate whether foreign investors have better information than domestic investors. We are motivated by (1) the controversy over the performance of foreign versus domestic investors and (2) market dynamics that require investors to adapt constantly. Using 123 positive and 81 negative news items from the Indonesia Stock Exchange (IDX), we find that foreign investors account for larger price movements before news announcements, suggesting that foreign investors tend to have better information than domestic investors. The result is robust, even after including the total trading volume, total number of transactions, and trading size. Further investigation reveals that foreign investors' small trades account for the largest price movements. Initiated trades account for larger price movements. Domestic investors have more foreign advantages than foreign investors. We also find that the foreign advantage disappears during non-event periods. Our results contrast with previous findings showing that domestic investors have better information than foreign investors. Our findings suggest that investor behavior is dynamic; investors adjust to their environment, which may lead to changes in their performance.

Analytical properties of Hasbrouck and generalized information shares

This paper discusses analytical properties of Hasbrouck information share (HIS) and generalized information share (GIS). We reject the conventional designation of lower and upper bounds for HIS. Moreover, we show the difference between the GIS across the two markets is larger than the corresponding difference between the average HIS. Thus, the dominance-satellite relationship is more prominent when using GIS to measure the role of price discovery. Using the data of dual-class shares of Berkshire Hathaway Inc., we find approximately 74.34% of the price discovery occurs in the B-shares market, which is consistent with the stealth trading hypothesis.

Volatility, trading activity and maximum lot amounts: Evidence from Borsa Istanbul

Intraday analyses of volatility-volume relation by decomposing the volume into number of trades and average trade size is measured in Borsa Istanbul equity market. Results confirm that the number of trades has more explanatory power over the short-term volatility comparably parallel with the existing literature. The unique maximum lot amount rule, classifying stocks according to their average trade size and limiting the order size for the stocks traded, has given the chance to control for the size of the trades naturally and analyse the relation of the volatility with other trading activity figures. The number of trades is the main factor explaining the variation in the short-term volatility parallel to the literature. Results show that heterogeneous effects arise from binding of trading constraints. The spread, which is mostly equal to the price tick, has the power to explain the volatility for high trading volumes significantly. Analyses show that stealth trading is possible for thinly traded stocks.

Tick Size and Informed Trading: Evidence from the Taiwanese Stock Market

We adopt the Sandås model for order-book equilibrium to examine informed trading on the Taiwanese stock market, a purely order-driven call-auction market. We find that adverse-selection cost is low for well-known stocks with high liquidity and low volatility, but cost is high for monitoring the order books of those stocks. Our empirical results show that the impact of adverse selection is greatest at the beginning of each trading day and that informed traders engage in stealth trading, supporting the stealth trading hypothesis. Finally, with the special tick size rules on the market, both adverse-selection cost and monitoring cost decline as tick size decreases.

Revisiting the Stealth Trading Hypothesis: Does Time-Varying Liquidity Explain the Size-Effect?

Large trades have a smaller price impact per share than medium-sized trades. So far, the literature has attributed this effect to the informational content of trades. In this paper, we show that this effect can arise from strategic order placement. We introduce the concept of a liquidity elasticity, measuring the responsiveness of liquidity demand with respect to changes in liquidity supply, as a major driver for a declining price impact per share. Empirical evidence based on Nasdaq stocks strongly supports theoretical predictions and shows that the aspect of liquidity coordination is an important complement to rationales based on asymmetric information.

The price impact of trade-size clustering: Evidence from an intraday analysis

Motivated by the prevalence of trade-size clustering in financial markets, this study examines whether this trading irregularity affects intraday price dynamics. Based on a global sample, we document that stronger trade-size clustering is associated with lower temporary price impact, consistent with the stealth trading hypothesis. Meanwhile, a positive interaction between clustering and permanent price changes further confirms that clustering trades convey information, suggesting that they originate from informed investors. After partitioning sizes into top, round, and non-round groups, we find that all are informative, despite the finding that top and round (non-round) sizes have more (less) clustering.

Trade-size clustering and price efficiency

Using a sample of 26 markets, this paper investigates if trade-size clustering affects price efficiency. Our results suggest that more clustering trades are associated with greater resemblance of a random walk, less pricing errors, and shorter price delays. Moreover, we examine three underlying mechanisms to explain how clustering improves efficiency. First, we show that clustering trades are informative, consistent with the idea that stealth traders leverage such tactics to convey private information to prices. Second, we discover that clustering trades are positively related to investor attention (stock liquidity), implying that informed clustering trades happen at the presence of enormous uninformed investors. High attention and liquid markets help reduce the trading friction, thereby prompting quick price adjustments to private information released by the stealth trading.

Round-number biases and informed trading in global markets

This paper investigates whether informed trading matters to round-number biases. We document the global presence of round-number biases by showing excessive buying (selling) pressure immediately below (above) a rounded threshold. Additionally, we demonstrate that trades surrounding 0-ending prices are likely to be initiated by informed traders who tend to buy (sell) at 9-ending (1-ending) prices. Moreover, small-sized (medium-sized) trades with 1-ending or 9-ending prices are revealed to be more informative and conducted persistently. Collectively, these findings seem to suggest that informed investors strategically engage in stealth trading by leveraging round-number biases of liquidity traders, which indirectly drives this anomaly in global markets.

Trade Size Preference of Informed Traders in Indian Equity Markets

ABSTRACTThis study utilized high frequency transactions data to analyze the trade size preference of informed traders in Indian equity markets. It is observed that informed traders at an aggregate level adopt stealth trading strategy, wherein they prefer medium sized trades over large sized trades in order to camouflage their private information. However, the stealth trading behavior varies across stocks, wherein informed traders prefer more large sized trades on firms that are part of an index compared to non-index firms. Trading behavior also varies across other market conditions. It has been noted that informed traders prefer large sized trades during periods of high market thickness, negative returns, and low volatility. This study also provides a rationale for such varied behavior of informed traders.

Trade Volume Choice and Price Discovery: Evidence from Deutsche BBrse

Using a comprehensive sample of stocks traded in Xetra system in German Stock Exchange, we first investigate the choice of trade volume by analyzing the trade size clustering and LOB-matched trades. Furthermore, we examine the role of these specific types of trade in the price discovery process. Our results confirm the stealth trading hypothesis and suggest that informed traders are likely to use the small-unrounded and small-matched market orders. In addition, the effects of other types of trades are either less informative or not significant.

Insider Trading Ahead of Cyber Breach Announcements

Stock market reactions to cybersecurity breach announcements are generally negative. In virtually all cases, information asymmetry exists between firm management and investors between the date of cybersecurity breach discovery and the public announcement of the breach. We find significant evidence of opportunistic insider trading, with insiders saving an average of $35,009 due to their timely selling in the three months prior to the announcement of a cybersecurity breach. Late filing violations by insiders, which are indicative of stealth trading, are more likely to occur near the announcement of a cyber breach. We also find that the bulk of opportunistic trading tends to occur 55 to 72 days before the public announcement. The results lend support to the SEC’s recently announced goal of tightening restrictions on insider trading ahead of cyber breach announcements, and we make several policy recommendations based on our findings.

Size and information revelation in securities trading

ABSTRACTWe examine differences in information content between order submission sizes and trade sizes by U.S. equity traders. Increasing (decreasing) order submission (trade) size is reflective of information. The result suggests that better-informed traders want to trade in a large size, but that they engage in stealth trading practices or break larger orders into smaller sizes in order to conceal information. While prior studies tend to narrowly focus on trade executions at the market-centre level, our findings indicate that order submission size varies significantly from trade size and that both sizes are informative about future prices, albeit in an inverse manner.

ODD LOT ORDER AGGRESSIVENESS AND STEALTH TRADING

AbstractWe investigate the degree to which orders are aggressively priced, paying particular attention to odd lot orders, and examine whether odd lot orders are being successfully used in stealth trading strategies. We find that odd lot orders execute at higher frequencies than larger orders, which is due to odd lot orders being aggressively priced. We find that microstructure changes have not altered the nature of price aggressiveness, but its determinants hold different explanatory power for odd lot orders. We find evidence that informed traders are shredding their orders into odd lot orders and stealth trading is permeating odd lot denominations.

Reexamination of the Stealth Trading Hypothesis: The Role of Liquidity Provision

Reexamination of the Stealth Trading Hypothesis: The Role of Liquidity Provision

Short Selling and the Cross-Section of CorporateBond Returns

This article studies the effect of short selling in the equity market on corporate bond returns. We show that firms with heavily shorted shares or large short-trade sizes experience significantly negative future bond returns. Further tests indicate that the relationship between short-trade size and subsequent bond returns is more consistent with stealth trading of short sellers. The impact of short selling on bond returns is robust to various controls for risk, liquidity, and other pricing factors. In examining the information source of short selling, we find that firms associated with heavy shorting activities or large short-trade sizes are likely to subsequently experience negative earnings surprises, higher credit risk, and reduced dividends. The evidence provides little support for the overvaluation argument. Overall, the results are consistent with the proposition that short trades in the equity market exert important valuation consequences in the corporate bond market.

Considering all microstructure effects: The extension of a trade indicator model

By considering various market microstructure effects, this letter proposes a comprehensive trade indicator model incorporating trade duration, order sizes, bid–ask spreads, and market depth into a unified framework. Examining the intraday price behavior of the KOSPI200 futures market, we find that (i) fast trading indicates informed trading, (ii) stealth trading does not prevail, (iii) order-processing costs reach economies of scale, and (iv) liquidity significantly affects investors’ order submission decisions in the highly liquid market.

Odd Lot Order Aggressiveness and Stealth Trading

This study investigates the degree to which orders are aggressively priced, paying particular attention to odd lot orders, and examines whether odd lot orders are being successfully used in stealth trading strategies. We find that odd lot orders execute at higher frequencies, which is due to odd lot orders being disproportionally aggressively priced. We find that microstructure changes have not altered the nature of price aggressiveness, but its determinants hold different explanatory power for odd lot orders. We find strong evidence that informed traders are shredding their orders into odd lot orders and stealth trading is permeating odd lot denominations.

The price impact of futures trades and their intraday seasonality

This study examines the price impact of futures trades and their intraday seasonality by analyzing the continuous trading session dataset of KOSPI 200 futures, including the opening and closing periods. For this purpose, the study analyzes the futures dataset that contains information on transaction times, trade directions, order sizes, and the types of investors initiating the transactions. The results suggest several novel findings. First, a substantial portion of the price impact of futures trades is persistent, indicating the presence of informed trading in the futures market. Second, informed trading is concentrated in the opening period and liquidity trading is concentrated in the closing period of the continuous trading session. Third, small trades usually have a greater price impact than large ones, supporting the existence of stealth trading by futures traders. Fourth, trades by institutional investors have a greater price impact than those by individuals, suggesting that institutional investors are better informed and/or more sophisticated than individual investors in the futures market.

Adverse selection and the presence of informed trading

Abstract We combine two concepts of informed trading – contrarian trades and stealth trading – to develop proxies for the probability of informed trading. These proxies are used to test the link between informed trading and adverse selection as measured by bid–ask spreads and stock illiquidity. The estimation results show that these proxies, which are based on the probability of contrarian trading (PC) and progressively refined thereon, are all highly significantly positive in various empirical specifications of the cross-sectional determinants of spreads and illiquidity across stocks, and after controlling for important firm characteristics and trading factors. The robustness of our PC-based proxies for informed trading in these analyses, especially for the further refined measures, suggests that they successfully capture the adverse selection component of bid–ask spreads and illiquidity due to information asymmetry.