Price impact of block trades: the curious case of downstairs trading in the EU emissions futures market

Using high-frequency data from the European Climate Exchange (ECX), we examine the determinants of price impact of €21 billion worth of block trades during 2008–2011 in the European carbon market. We find that wider bid-ask spreads and volatility are characterised by a smaller price impact. Larger levels of price impact are more likely to occur during the middle of the trading day, specifically the four-hour period between 11 a.m. and 3 p.m., than during the first or final hours. Purchase block trades induce a relatively smaller price impact on price run-up, while sell block trades exhibit a larger price impact on price run-up. We conclude that block trades on the ECX induce less price impact than in equity or conventional futures markets, and that a significant proportion of the effects contradict findings on block trades in those markets; thus, we provide the first evidence of the curious bent to block trading in the European Union emissions trading scheme.     

Information-Based Trading and Price Improvement

Abstract:  In this study we test the information hypothesis of price improvement. Our results show that price improvement is negatively related to both the probability of information-based trading and the price impact of trades. We interpret these results as evidence that liquidity providers selectively offer price improvements according to the information content of trades. We also show that liquidity providers offer greater (and more frequent) price improvements when they are at the NBBO, and for stocks with wider spreads, fewer trades, or smaller trade sizes relative to the quoted depth. Buyer-initiated trades receive smaller (larger) price improvements than seller-initiated trades on the NYSE (NASDAQ).     

Stealth trading: The case of the Tokyo Stock Exchange

The stealth trading hypothesis asserts that informed traders trade strategically by breaking up their orders so as to more easily hide among the liquidity traders. Using data for the Tokyo Stock Exchange (TSE), a pure order-driven market, we find evidence that price changes are driven by small- and medium-size trades, with small trades making the greatest contribution to price change relative to their contribution to trading volume. We also find that large trades explain a greater portion of the cumulative price change on high volatility days. Hence, our results support the stealth trading hypothesis for the TSE.     

Trade size clustering and the cost of trading at the London Stock Exchange

For the London Stock Exchange, this paper investigates differences in trading costs between market maker (off-book) and order book trades, in the context of clustering in trade sizes and prices. We report several substantial findings. Even after controlling for differences in trade size, the realised spread measure is lower for off-book trades. For the order book, trade size clustering is not associated with differences in transaction costs nor with differences in the information content of trades. For the off-book market, trades in clustered (popular) sizes carry significantly more information than non-clustered trades. Despite the significant differences in the price impact estimates between the order book and off-book, we show that traders placing large orders off-book are still better off than trading via the order book as they benefit from a large discount from the current midpoint price. Additionally, we highlight that price and size clustering tend to occur simultaneously rather than being substitutes in this market setting.     

Information-based trading,price impact of trades,and trade autocorrelation

In this study we show that both the price impact of trades and serial correlation in trade direction are positively and significantly related to the probability of information-based trading (PIN). The positive relation remains significant even after controlling for the effects of stock attributes. Higher trading activity (i.e., shorter intervals between trades) induces both larger price impact and stronger positive serial correlation in trade direction. The effect of time interval between trades on quote revision is stronger for stocks with higher PIN values. These results provide direct empirical support for the information models of trade and quote revision.     

Permanent trading impacts and bond yields

We analyse four years of transaction data for euro-area sovereign bonds traded on the MTS electronic platforms. In order to measure the informational content of trading activity, we estimate the permanent price response to trades. We not only find strong evidence of information asymmetry in sovereign bond markets, but also show the relevance of information asymmetry in explaining the cross-sectional variations of bond yields across a wide range of bond maturities and countries. Our results confirm that trades of more recently issued bonds and longer maturity bonds have a greater permanent effect on prices. We compare the price impact of trades for bonds across different maturity categories and find that trades of French and German bonds have the highest long-term price impact in the short maturity class, whereas trades of German bonds have the highest permanent price impact in the long maturity class. More importantly, we study the cross-section of bond yields and find that after controlling for conventional factors, investors demand higher yields for bonds with larger permanent trading impact. Interestingly, when investors face increased market uncertainty, they require even higher compensation for information asymmetry.     

Informed trading and the price impact of block trades: A high frequency trading analysis

Using high frequency data from the London Stock Exchange (LSE), we investigate the relationship between informed trading and the price impact of block trades on intraday and inter-day basis. Price impact of block trades is stronger during the first hour of trading; this is consistent with the hypothesis that information accumulates overnight during non-trading hours. Furthermore, private information is gradually incorporated into prices despite heightened trading frequency. Evidence suggests that informed traders exploit superior information across trading days, and stocks with lower transparency exhibit stronger information diffusion effects when traded in blocks, thus informed block trading facilitates price discovery.     

How efficiency shapes market impact

We develop a theory for the market impact of large trading orders, which we call metaorders because they are typically split into small pieces and executed incrementally. Market impact is empirically observed to be a concave function of metaorder size, i.e. the impact per share of large metaorders is smaller than that of small metaorders. We formulate a stylized model of an algorithmic execution service and derive a fair pricing condition, which says that the average transaction price of the metaorder is equal to the price after trading is completed. We show that at equilibrium the distribution of trading volume adjusts to reflect information, and dictates the shape of the impact function. The resulting theory makes empirically testable predictions for the functional form of both the temporary and permanent components of market impact. Based on the commonly observed asymptotic distribution for the volume of large trades, it says that market impact should increase asymptotically roughly as the square root of metaorder size, with average permanent impact relaxing to about two-thirds of peak impact.     

The interaction between opening call auctions and ongoing trade: Evidence from the NYSE

We investigate the impact that the opening batch has on trading for the remainder of the day and what impact the prior day's trading has on the subsequent day's open. Traders have an interest in these trading impacts as their trades may cluster around opening and closing time periods. We find that the larger the volume in the opening batches, the greater the volume across the day. We also find the prior day's volume being positively related to the subsequent day's opening volume. Combined, these results suggest a continuing pattern of trade volume rolling from one day to the next. Additionally, we find that the spread in the continuous market can be partially attributed to the price change in the opening batch. We also find evidence of opening trade price reversals. Combined with the absence of price reversals following the opening trade, we conclude that the opening process may be more efficient at handling information than the continuous market.     

Legal insider trading and market efficiency

Does legal insider trading contribute to market efficiency? Using refinements proposed in the recent microstructure literature, we analyzed the information content of legal insider trading. We used data on 2110 companies subject to 59,244 aggregated daily insider trades between January 1995 and the end of September 1999. Our main finding is that, even though financial markets do not respond strongly in terms of abnormal returns to insider trading activities, the significant change in price sensitivity to relative order imbalance due to abnormal insider trades reveals that price discovery is hastened on insider trading days.     

Further analysis of the liquidity and information components of institutional orders: Active versus passive funds

Previous research examining the price impact of institutional trading concludes that index funds incur higher liquidity costs due to the higher demand for trading immediacy. However, this conclusion has only been inferred by comparing the total price impact of active and index funds. This study extends the literature by decomposing the price impact of both active and index funds' trades into liquidity (temporary) and information (permanent) components. Index fund trades incur higher liquidity costs and generate lower returns than active funds' trades. Indeed, the evidence presented in this study reveals the execution costs of index funds' trades are entirely liquidity-driven.     

Impact of MiFID II tick-size regime on equity markets—Evidence from the LSE

This study investigates the impact of MiFID II on the London Stock Exchange. We find that a tick-size reduction leads to lower bid–ask spreads, lower trade values, reduced cost of trading at and beyond the best bid-offer, an acceleration of quote updates, an increase in aggressive trades and a reduction in price impact. Increased tick size widens spreads and increases trading costs. Step functions reveal that liquidity adjusts opposite to the tick change. To determine if impacts are proportional, we identify potential functions that predict cost changes with tick updates, implying that traders adjust their trade sizes according to the new tick levels.     

Multiple-limit trades: empirical facts and application to lead–lag measures

Order splitting is a standard practice in trading: traders constantly scan the limit order book and choose to limit the size of their market orders to the quantity available at the best limit, thereby controlling the market impact of their orders. In this article, we focus on the other trades, multiple-limit trades that go through the best available price in the order book, or ‘trade-throughs’. We provide various statistics on trade-throughs: frequency, volume, intraday distribution, market impact, etc., and present a new method for the measurement of lead–lag parameters between assets, sectors or markets.     

Assessing the profitability of intraday opening range breakout strategies

Is it possible to beat the market by mechanical trading rules based on historical and publicly known information? Such rules have long been used by investors and in this paper, we test the success rate of trades and profitability of the Open Range Breakout (ORB) strategy. An investor that trades on the ORB strategy seeks to identify large intraday price movements and trades only when the price moves beyond some predetermined threshold. We present an ORB strategy based on normally distributed returns to identify such days and find that our ORB trading strategy result in significantly higher returns than zero as well as an increased success rate in relation to a fair game. The characteristics of such an approach over conventional statistical tests is that it involves the joint distribution of low, high, open and close over a given time horizon.     

Transaction duration and asymmetric price impact of trades—Evidence from Australia

This paper investigates the asymmetric price impact of buyer and seller initiated trades and the informational role of the trade duration. Using trade data from the Australian Stock Exchange (ASX), our results indicate that buyer initiated trades increase the ask price more than the bid price, and seller initiated trades decrease the bid price more than the ask price. The transaction duration is modeled in a Box-Cox ACD framework. The unexpected portion of the duration is found to play a more significant role in causing price impact in both purchases and sales than the expected duration. A trade shortly after the previous trade results in higher price impact than one after a long period. We found evidence that increased trading activity is associated with larger price impact, therefore implying a higher degree of information-based trading.     

Preferenced Trading,Quote Competition,and Market Quality: Evidence from Decimalization on the NYSE

We examine the impact of decimalization on preferenced trading in NYSE‐listed stocks and show a significant decline in preferenced trading around decimalization. For the largest NYSE stocks, the total decline is nearly 22%. We also find a negative correlation between the changes in preferenced trading and the changes in quote competition intensity, and a positive correlation between the changes in preferenced trading and the changes in spreads. Consistent with the cream skimming hypothesis, we find that abnormal changes in information asymmetry cost for NYSE trades are positively correlated with the changes in preferenced trading.     

Brokered versus dealer markets: Impact of proprietary trading with transaction fees

In this study, we consider a one-period financial market with a dealer/broker and an infinite number of investors. While the dealer who trades on his own account (with proprietary trading) simultaneously sets both the transaction fee and the asset price, the broker who brings investors' orders to the market (with no proprietary trading) sets only the transaction fee, given that the price is determined according to the market-clearing condition among investors. We analyze the impact of proprietary trading on the asset price, transaction fee, trading volume, and the welfare of investors. We find that the bid and ask prices set by the dealer who can engage in proprietary trading are more favorable to average investors. As a result, both the trading volume and the transaction fee increase, and social welfare improves.     

Market Structure and Transaction Costs of Index CDSs

Despite regulatory efforts to promote all-to-all trading, the post–Dodd-Frank index credit default swap market remains two-tiered. Transaction costs are higher for dealer-to-client than interdealer trades, but the difference is explained by the higher, largely permanent, price impact of client trades. Most interdealer trades are liquidity motivated and executed via low-cost, low-immediacy trading protocols. Dealer-to-client trades are nonanonymous; they almost always improve upon contemporaneous executable interdealer quotes, and dealers appear to price discriminate based on the perceived price impact of trades. Our results suggest that the market structure is a consequence of the characteristics of client trades: relatively infrequent, large, and differentially informed.     

Individual Investors and Volatility

We show that retail trading activity has a positive effect on the volatility of stock returns, which suggests that retail investors behave as noise traders. To identify this effect, we use a reform of the French stock market that raises the relative cost of speculative trading for retail investors. The daily return volatility of the stocks affected by the reform falls by 20 basis points (a quarter of the sample standard deviation of the return volatility) relative to other stocks. For affected stocks, we also find a significant decrease in the magnitude of return reversals and the price impact of trades.     

Strategic trading and learning about liquidity

Many practitioners point out that the speculative profits of institutional traders are eroded by the difficulty in gauging the price impact of their trades. In this paper, we develop a model of strategic trading where speculators face such a dilemma because of incomplete information about time-varying market liquidity. Unlike the competitive market makers that they trade against, informed traders do not know the distribution of liquidity (“noise”) trades. Instead, they have to learn about liquidity from past prices and trading volume. This learning implies that strategic trades and market statistics such as informational efficiency are path-dependent on past market outcomes. Our paper also has normative implications for practitioners.