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Vestigial Tails: Floor Brokers at the Close in Modern Electronic Markets
... Moreover, also human brokers are considered by some to be slower and more error-prone than algorithms. In addition, some researchers also argued that fully electronic markets are more efficient than those featuring a certain degree of human intervention [284]. Researchers analyzed NYSE's hybrid auction structure, which normally allows floor traders to submit their last orders of the day up to 10 s before the market's close, whereas those coming through electronically have to make theirs 10 min before its end. ...
... Then, to evaluate the effect of an electronic-only market, scholars compared market efficiency while the NYSE was operating only remotely, with its normal (i.e., hybrid) mode of operation. Interestingly, they found that auctions have become more efficient since the NYSE moved entirely online [284]. ...
This book revises the strategic objectives of Information Warfare, interpreting them according to the modern canons of information age, focusing on the fabric of society, the economy, and critical Infrastructures. The authors build plausible detailed real-world scenarios for each entity, showing the related possible threats from the Information Warfare point of view. In addition, the authors dive into the description of the still open problems, especially when it comes to critical infrastructures, and the countermeasures that can be implemented, possibly inspiring further research in the domain.
This book intends to provide a conceptual framework and a methodological guide, enriched with vivid and compelling use cases for the readers (e.g. technologists, academicians, military, government) interested in what Information Warfare really means, when its lenses are applied to current technology. Without sacrificing accuracy, rigor and, most importantly, the big picture of Information Warfare, this book dives into several relevant and up-to-date critical domains.
The authors illustrate how finance (an always green target of Information Warfare) is intertwined with Social Media, and how an opponent could exploit these latter ones to reach its objectives. Also, how cryptocurrencies are going to reshape the economy, and the risks involved by this paradigm shift. Even more compelling is how the very fabric of society is going to be reshaped by technology, for instance how our democratic elections are exposed to risks that are even greater than what appears in the current public discussions. Not to mention how our Critical Infrastructure is becoming exposed to a series of novel threats, ranging from state-supported malware to drones. A detailed discussion of possible countermeasures and what the open issues are for each of the highlighted threats complete this book.
This book targets a widespread audience that includes researchers and advanced level students studying and working in computer science with a focus on security. Military officers, government officials and professionals working in this field will also find this book useful as a reference.
... Moreover, also human brokers are considered by some to be slower and more error-prone than algorithms. In addition, some researchers also argued that fully electronic markets are more efficient than those featuring a certain degree of human intervention [284]. Researchers analyzed NYSE's hybrid auction structure, which normally allows floor traders to submit their last orders of the day up to 10 s before the market's close, whereas those coming through electronically have to make theirs 10 min before its end. ...
... Then, to evaluate the effect of an electronic-only market, scholars compared market efficiency while the NYSE was operating only remotely, with its normal (i.e., hybrid) mode of operation. Interestingly, they found that auctions have become more efficient since the NYSE moved entirely online [284]. ...
Since the dawn of Humanity, the progress machine tirelessly introduced tools and resources that facilitated our everyday tasks. Over the years, new technologies have continually changed society with novel discoveries and inventions that proved capable of greatly improving human life. Historically, many of the processes that radically changed human lifestyle occurred gradually. However, in the past few decades, modern technology has enabled a fast and radical change of our society, modifying our habits, production means, and in some cases the very essence of work, through the widespread adoption of a plethora of new devices comprising smartphones, voice assistants, chatbots and smartwatches that made our lives faster, easier, and funnier. Technology is also introducing new habits and addictions, changing every aspect of our society such as personal interactions, education, communication, financial services, physical goods production, logistics, and entertainment. This is happening in parallel with a wild race to the digitization of information.
... Moreover, also human brokers are considered by some to be slower and more error-prone than algorithms. In addition, some researchers also argued that fully electronic markets are more efficient than those featuring a certain degree of human intervention [284]. Researchers analyzed NYSE's hybrid auction structure, which normally allows floor traders to submit their last orders of the day up to 10 s before the market's close, whereas those coming through electronically have to make theirs 10 min before its end. ...
... Then, to evaluate the effect of an electronic-only market, scholars compared market efficiency while the NYSE was operating only remotely, with its normal (i.e., hybrid) mode of operation. Interestingly, they found that auctions have become more efficient since the NYSE moved entirely online [284]. ...
Technology has, to different degrees, always been part of the financial world, starting from the 1950s with the introduction of credit cards and ATMs, passing through electronic trading floors and personal finance apps, until present days where technologies such as Artificial Intelligence (AI), High-Frequency Trading (HFT), and cryptocurrencies are widespread. The prominent role of technology in finance has become so important as to obtain a specific term to describe the intersection between the two—that is, FinTech. A portmanteau of “financial technology,” FinTech refers to the application of new technological advancements to products and services in the financial industry. The definition is rather broad and also encompasses “innovative ideas that improve financial service processes by proposing technological solutions according to different business situations, while the ideas could also lead to new business models or even new businesses.” Following the previous definitions, FinTech cannot be categorized as a brand new industry but rather as one that has evolved at an extremely rapid pace.
... Brogaard et al. (2014) demonstrate that High-Frequency Trading (HFT) enhances market efficiency by aligning with permanent price changes and countering temporary mispricings. More recently, Hu and Murphy (2020) found that the full automation of NYSE's closing auctions led to improved auction quality. ...
This paper examines the impact of algorithmic trading on market quality using a unique NASDAQ OMX Nordic dataset from 2010–2011. We classify traders into algorithmic, institutional, professional, and retail categories. Using two-way fixed effects models and instrumental variables estimation, we find that algorithmic traders enhance liquidity by reducing bid-ask spreads by 0.28 basis points relative to retail traders, with similar effects from institutional traders. These effects persist during high volatility periods, while professional traders are associated with wider spreads. Surprisingly, retail traders emerge as significant liquidity providers, while algorithmic traders exhibit higher order cancellation rates. These findings contribute to the debate on algorithmic trading's role in modern markets and offer implications for market design and regulation.
... As Hu and Murphy (2020) state, "the lack of a complete reversal during the reopening period suggests that the larger dislocations may be unrelated to the floor closure." ...
Although algorithmic trading now dominates financial markets, some exchanges continue to use human floor traders. On March 23, 2020 the NYSE suspended floor trading because of COVID‐19. Using a difference‐in‐differences analysis around the closure of the floor, we find that floor traders are important contributors to market quality. The suspension of floor trading leads to higher spreads and larger pricing errors for treated stocks relative to control stocks. To explore the mechanism, we exploit two partial floor reopenings that have different characteristics. Our finding suggests that in‐person human interaction facilitates the transfer of valuable information that algorithms lack.
... Recent papers by Bogousslavsky and Muravyev (2020) and Hu and Murphy (2021) also study closing auctions. Bogousslavsky and Myravyev document that closing auction prices deviate from the midpoints of the final bid-ask spread quotes before closing auctions. ...
Closing auction volume steadily increased over the last decade, and it reached a peak of about 10% of the total trading volume in 2019. We examine the price impact and resiliency of closing auctions, and we compare closing auction liquidity in Nasdaq and the NYSE. The NYSE offers more depth. In both exchanges, it takes about 3–5 days for the temporary component of the price impact to fully dissipate. Trading strategies that exploit this price impact and its reversals are significantly profitable.
... Although floor brokers may appear to play a less significant role in providing liquidity than decades ago, NYSE"s hybrid auction format, still allows floor brokers to manually submit nearly 35% all of orders (NYSE, 2019). Hu and Murphy (2020) show that hidden floor broker volume tends to peak toward the end of the closing auction period. However, Hu and Murphy also cite NYSE"s own analysis that found accumulated hidden discretionary "D-Orders", which have essentially replicated the manual role of floor brokers in handling contra-side orders, dropped from 30% to 0% during the closing auction period during the NYSE floor close. ...
We examine the impact of COVID-19 on market structure in the U.S. Specifically, we analyze the impact of both the COVID-19-induced market uncertainty period as well as the suspension of the NYSE floor on trading dynamics such as market fragmentation, algorithmic trading, and hidden liquidity in the market. During both the heightened market uncertainty and NYSE floor suspension periods, we find a significant increase in hidden liquidity yet significant decreases in both algorithmic trading and market fragmentation. However, despite withdrawing from the market during this period, remaining algorithmic traders appear to improve market quality. Our results indicate that COVID-19 had a significant impact on order routing, pre-trade transparency, and automated trading.
... 4 The Markets in the Financial Instruments Directive (MiFID) was created by the European Union in 2004 to promote the of European financial markets. 5 See Atkins and Dyl (1997); Hu and Murphy (2021); Jain (2005); and Bessembinder and Rath (2008). 6 See Nasdaq 2018 10K report, available at http://ir.nasdaq.com/financials/annual-reports, ...
This paper reviews the up-to-date theoretical, empirical, and experimental literature related to the trading venue choice in the context of the fragmented equity markets. We provide a brief background on the history of trading fragmentation in the equity market and its determinants. We discuss the direct and indirect impacts of the market fragmentation on market quality in various dimensions, including liquidity, volatility, and price efficiency. Next, we identify possible determinants and channels from theoretical and empirical studies that could explain order routing decisions and present the possible directions for future research. Finally, we discuss the major regulatory reforms in the U.S. equity market on routing venue decisions. This topic is relevant in current times when phenomena such as “GameStop Frenzy” have drawn significant attention to commission-free trading venues.
... In the European Union, since 2018, all regulated exchanges are required to apply volatility curbs in continuous trading as well as in call auctions. 2 In the United States, the efficiency of CCA prices are questioned by recent studies by Bogousslavsky and Muravyev (2020) and Hu and Murphy (2020). ...
To improve the efficiency of the closing price, many equity exchanges apply volatility extensions to their closing call auctions (CCAs). If an imminent auction execution implies a large price change, the order submission period is extended to let traders reconsider their orders. This paper uses the introduction of closing auction volatility extensions at NASDAQ Nordic to provide the first analysis of the effects of such mechanisms. We find that the volatility extensions reduce transitory volatility and deter price manipulation at the close. Consistent with increased trust in the mechanism, the CCA attracts higher volumes after the change.
We present broad-based evidence that the monthly payment cycle induces systematic patterns in liquid markets around the globe. First, we document temporary increases in the costs of debt and equity capital that coincide with key dates associated with month-end cash needs. Second, we present direct and indirect evidence on the role of institutions in the genesis of these patterns and derive estimates of the associated costs borne by market participants. Third, and finally, we investigate the limits to arbitrage that prevent markets from functioning efficiently. Our results indicate that many investors and their agents, including mutual funds, suffer from liquidity-related trading.
Received January 16, 2018; editorial decision January 2, 2019 by Editor Robin Greenwood. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
Modern markets are characterized by speed differentials, with some traders being fractions of a second faster than others. Theoretical models suggest that such differentials may have both positive and negative effects on liquidity and gains from trade. We examine these effects by studying a series of exogenous weather episodes that temporarily remove the speed advantages of the fastest traders by disrupting their microwave networks. The disruptions are associated with lower adverse selection and lower trading costs. In additional analysis, we show that the long‐term removal of speed differentials results in similar effects and also increases gains from trade.
The Fix for precious metals is a global pricing benchmark that provides pricing and liquidity provision for market participants. We exploit the gradual change in the century old auction process to quantify the efficiencies related to more transparent pricing. Our focus is in the market impact of this change on exchange listed products. We find that reforms to the Fix have reduced quoted and effective bid‐ask spreads and improved overall market depth. The results imply a positive spillover effect stemming from timelier and more accurate pricing information. The conditions under which we observe the benefits from transparency are related to product liquidity and the degree of market segmentation.
Closing prices on financial exchanges are often used as reference prices in other contracts. As such, the robustness of the process determining closing prices is an important feature of exchanges. This paper examines whether the 2012 change in the Chicago Board of Trade's (CBT) closing price procedure made reference prices more robust, especially regarding potential manipulation. We propose a theoretical model exploring incentives to manipulate reference prices under two alternative closing price regimes. We test several predictions of the model using a proprietary data set comprised of individual transactions in CBT corn futures, and find empirical support for these predictions.
In second price Internet auctions with a fixed end time, such as those on eBay, many bidders submit their bids in the closing minutes or seconds of an auction. We propose an internet auction model, in which very late bids have a positive probability of not being successfully submitted, and show that late bidding in a fixed deadline auction can occur at equilibrium in auctions both with private values and with uncertain, dependent values. Late bidding may also arise out of equilibrium, as a best reply to incremental bidding. However, the strategic advantages of late bidding are severely attenuated in auctions that apply an automatic extension rule such as auctions conducted on Amazon. Field data show that there is more late bidding on eBay than on Amazon, and this difference grows with experience. We also study the incidence of multiple bidding, and its relation to late bidding.
The NYSE opened the limit-order book to off-exchange traders during trading hours. We address the welfare implications of this change in market structure. We model a market similar to the auction that the exchange uses to open the trading day. We consider two different environments. In the first, only the specialist sees the limit-order book, while in the second the information in the book is available to all traders. We compare equilibria and find that traders who demand liquidity are better off when the book is open while liquidity suppliers are better off when the book is closed.
The price and trading volume behaviors of individual stocks in the Standard and Poor's 500 Stock Index (S&P 500) are analyzed on stock index futures expiration days, a time when the market is known to be subject to heavy program trading. The price behavior of stocks that are subject to program trading is shown to be very similar to stocks that are not. Stocks that decline in price in the last half hour Friday tend to increase in price at the opening on Monday and vice versa. The Monday reversal as a fraction of the Friday price change is only slightly higher for the S&P 500 stocks than for non-S& P 500 stocks, indicating that the price reversals reflect, for the most part, the bid-ask spreads of the individual stocks. Trading volume in the last half hour of expiration days is shown to be substantially higher than normal. Copyright 1990 by the University of Chicago.
Opening mechanisms play a crucial role in information aggregation following the overnight nontrading period. This article
examines the process of price discovery at the New York Stock Exchange single-price opening auction. We develop a theoretical
model to explain the determinants of the opening price and test the model using order-level data. We show that the presence
of designated dealers facilitates price discovery relative to a fully automated call auction market. This is consistent with
specialists extracting information from observing the evolution of the limit order book. In addition, the specialist's opening
trade reflects noninformational factors such as price stabilization requirements.
Various markets, particularly NASDAQ, have been under pressure from regulators and market participants to introduce call auctions for their opening and closing periods. We investigate the performance of call markets at the open and close from a unique natural experiment provided by the institutional structure of the London Stock Exchange. As well as a call auction, there is a parallel ¶off-exchange¶ dealership system at both the market's open and close. Although the call market dominates the dealership system in terms of price discovery, we find that the call suffers from a high failure rate to open and close trading, especially on days characterized by difficult trading conditions. In particular, the call's trading costs increase significantly when (a) asymmetric information is high, (b) trading is expected to be slow, (c) order flow is unbalanced, and (d) uncertainty is high. Furthermore, traders' resort to call auctions is negatively correlated with firm size, implying that the call auction is not the optimal method for opening and closing trading of medium and small sized stocks. We suggest that these results can be explained by thick market externalities.
I show that frequent batch auctions for stocks have the potential to reduce the severity of stock price crashes when they occur. For a given sequence of orders from a continuous electronic limit order book market, matching orders using one-second apart batch auctions results in nearly the same trades and prices. Increasing the time interval between auctions to one minute significantly reduces the severity stock price crashes. In spite of this and other advantages pointed out in the literature, frequent batch auctions have not caught on. There is a need for carefully designed market experiments to understand why and what aspect of reality academic research may be missing.
The New York Stock Exchange (NYSE) is the only U.S. equities exchange that offers parity allocation of all trades. Parity requires that orders from each floor broker, the designated market maker, and the top of the electronic limit order book trade together. Thus, floor trading interests can trade ahead of equally-priced, previously arriving orders in the limit order book. The presumption on the NYSE is that floor traders provide valuable services to the investing public and one approach to remunerating them for these services is deviating from strict time priority. Our research attempts to quantify the cost of this privilege.
We link investor heterogeneity to the persistence of the overnight and intraday components of returns. We document strong overnight and intraday firm-level return continuation along with an offsetting cross-period reversal effect, all of which lasts for years. We look for a similar tug of war in the returns of 14 trading strategies, finding in all cases that profits are either earned entirely overnight (for reversal and a variety of momentum strategies) or entirely intraday, typically with profits of opposite signs across these components. We argue that this tug of war should reduce the effectiveness of clienteles pursuing the strategy. Indeed, the smoothed spread between the overnight and intraday return components of a strategy generally forecasts time variation in that strategy's close-to-close performance in a manner consistent with that interpretation. Finally, we link cross-sectional and time-series variation in the decomposition of momentum profits to a specific institutional tug of war.
Independent technological glitches forced two separate trading halts on different U.S. exchanges during the week of July 6, 2015. During each halt, all other exchanges remained open. We exploit exogenous variation provided by this unprecedented coincidence, in conjunction with a proprietary data set, to identify the causal impact of Designated Market Maker (DMM) participation on liquidity. When the voluntary liquidity providers on one exchange were removed, liquidity remained unchanged; when DMMs were removed, liquidity decreased market-wide. We find evidence consistent with the idea that these DMMs, despite facing only mild formal obligations, significantly improve liquidity in the modern electronic marketplace.
Size-discovery mechanisms allow large quantities of an asset to be exchanged at a price that does not respond to price pressure. Primary examples include “workup” in Treasury markets, “matching sessions” in corporate bond and CDS markets, and block-trading “dark pools” in equity markets. By freezing the execution price and giving up on market-clearing, size-discovery mechanisms overcome concerns by large investors over their price impacts. Price-discovery mechanisms clear the market, but cause investors to internalize their price impacts, inducing costly delays in the reduction of position imbalances. We show how augmenting a price-discovery mechanism with a size-discovery mechanism improves allocative efficiency.
Received November 9, 2015; editorial decision October 28, 2016 by Editor Itay Goldstein.
The introduction of widely available ultra high-frequency data sets over the past decade has spurred interest in empirical market microstructure. Intraday transaction-by-transaction dynamics of asset prices, volume, and spreads are available for analysis. Classic asset pricing research assumes only that prices eventually reach their equilibrium value; the route taken and speed of achieving equilibrium are not specified. The introduction of widely available ultra-high-frequency data sets over the past decade has spurred interest in empirical market microstructure. The black box determining equilibrium prices in financial markets has been opened up. Intraday transaction-by-transaction dynamics of asset prices, volume, and spreads are available for analysis. These vast data sets present new and interesting challenges to econometricians. While artificially discretizing the time intervals at which prices (or other marks) is a common practice in the literature, it does not come without cost. Different discretizing schemes trade of bias associated with temporally aggregating with variance. Averaging reduces the variability but blurs the timing of events.
We exploit an optional colocation upgrade at NASDAQ OMX Stockholm to assess how speed affects market liquidity. Liquidity
improves for the overall market and even for noncolocated trading entities. We find that the upgrade is pursued mainly by
participants who engage in market making. Those that upgrade use their enhanced speed to reduce their exposure to adverse
selection and to relax their inventory constraints. In particular, the upgraded trading entities remain competitive at the
best bid and offer even when their inventories are in their top decile. Our results suggest that increasing the speed of market-making
participants benefits market liquidity.
This article develops a theory in which concentrated-trading patterns arise endogenously as a result of the strategic behavior
of liquidity traders and informed traders. Our results provide a partial explanation for some of the recent empirical findings
concerning the patterns of volume and price variability in intraday transaction data.
We develop a dynamic model of a limit order market populated by strategic liquidity traders of varying impatience. In equilibrium, patient traders tend to submit limit orders, whereas impatient traders submit market orders. Two variables are the key determinants of the limit order book dynamics in equilibrium: the proportion of patient traders and the order arrival rate. We offer several testable implications for various market quality measures such as spread, trading frequency, market resiliency, and time to execution for limit orders. Finally, we show the effect of imposing a minimal price variation on these measures. Copyright 2005, Oxford University Press.
To minimize risks, we must learn more about how financial markets operate at ever faster rates, urges Mark Buchanan.
We examine the relationship between announcements of (a) market-on-close orders, (b) the price dynamics and (c) specialist trading on the New York Stock Exchange. We find that the closing order imbalance affects prices even prior to the announcement of the imbalance. This is consistent with investors expressing their demands through both market-on-close orders and direct purchases - so that some of the price impact could occur before the specialist's announcement of the imbalance. However, the specialist himself is trading prior to the announcement, which also helps explain why at least some of the price movement occurs before the dissemination of the imbalances. Consequently, the remaining investors are actually trading /against/ the direction of their closing imbalances and the specialist is /not/ helping to smooth investor demands. Because of the structure of the mechanism and the volatility of prices near the close (which is especially elevated at the deadline for market on close orders at 3:40 p.m.), this is an interesting context for studying how information gets reflected in price.
Automation and trading speed are increasingly important aspects of competition among financial markets.
Order revelation is a non-trivial process that depends on a market's rules of order handling and order information disclosure. As participants reveal their orders for a stock to a market, the book gets deeper, price is discovered and trading volume (quantity) is "found." However, for large participants, uncertainty about the pro…le of other traders in the market inhibits their order revelation, thereby distorting trading volume and reducing the gains from trade. These ine¢ ciencies are mitigated when participants can place multiple orders, and when submitted orders are displayed in an open book that e¤ectively permits participants to engage in non-binding pre-trade communication.
This paper presents a model of an order-driven market where fully strategic, symmetrically informed liquidity traders dynamically
choose between limit and market orders, trading off execution price and waiting costs. In equilibrium, the bid and ask prices
depend only on the numbers of buy and sell orders in the book. The model has a number of empirical predictions: (i) higher
trading activity and higher trading competition cause smaller spreads and lower price impact; (ii) market orders lead to a
temporary price impact larger than the permanent price impact, therefore to price overshooting; (iii) buy and sell orders
can cluster away from the bid-ask spread, generating a hump-shaped order book; (iv) bid and ask prices display a comovement
effect: after, e.g., a sell market order moves the bid price down, the ask price also falls, by a smaller amount, so the bid-ask
spread widens; (v) when the order book is full, traders may submit quick, or fleeting, limit orders.
We quantify the effects of closing price manipulation on trading characteristics and stock price accuracy using a unique sample of prosecuted manipulation cases. Based on these findings we construct an index of the probability and intensity of closing price manipulation. As well as having regulatory applications, this index can be used to study manipulation in the large number of markets and time periods in which prosecution data are not readily available.
The Paris Bourse (currently Euronext Paris) refined its trading system to include electronic call auctions at market closings in 1996 for its less-liquid Continuous B stocks and in 1998 for its more actively traded Continuous A stocks. This paper analyzes the effects of the innovation on market quality. Our empirical analysis of price behavior for two samples of firms (50 B stocks and 50 A stocks) for two different calendar dates (1996 and 1998) indicates that introduction of the closing calls has lowered execution costs for individual participants and sharpened price discovery for the broad market. We further observe that market quality is improved at market openings, albeit to a lesser extent. We suggest that a positive spillover effect explains the closing call's more pervasive impact.
The Singapore Exchange introduced opening and closing call auctions in August 2000. We find that the frequency of call trades is lower than on other markets. However, when auctions are used, the percentage of daily volume traded in the auction is high. Many days without call trades have quotes during the pre-call periods so that there is an opportunity for learning about equilibrium prices even when there are no call trades. Consistent with prior research, the introduction of call auctions enhances market quality at the open and the close. The call auctions also helped to address the issues that motivated their introduction in Singapore. That is, they increased the volume traded at the opening in initial public offerings and reduced the incidence of closing price manipulation.
Before the introduction of a call auction at the close, the last minute of trading at the Paris Bourse was the most active of the whole day. Even though the bid–ask spread increased substantially, the probability of large and aggressive orders increased, as did price volatility. In addition, both the one-minute returns and the proportion of partially hidden orders increased. In this paper, we develop an agency-based model of closing price manipulation, which can account for these phenomena. In addition, we discuss the optimal closing price mechanism under manipulation.
We show that the consolidation of orders is important for producing efficient prices, especially during times of high liquidity demand. The NYSE's centralized opening call market performs better than Nasdaq's decentralized opening process on typical trading days. The NYSE is much better than Nasdaq on witching days when index arbitrage activity subjects S P 500 stocks to large, predictable, and mostly informationlessorder flow around quarterly futures contract expirations. Nasdaq opening price efficiency improves to NYSE levels once Nasdaq initiates a consolidated opening call in November 2004, but prices on the decentralized Nasdaq remain less efficient at other times of day.
Before the opening of the Paris Bourse, traders place orders and indicative prices are set. This offers a laboratory to study empirically the tatonnement process through which markets discover equilibrium prices. Since preopening orders can be revised or canceled before the opening, indicative prices could be noise. We test this against the hypothesis that preopening prices reflect learning. Early in the preopening the noise hypothesis is not rejected. As the opening gets closer, the informational content and efficiency of prices increase and the learning hypothesis is not rejected. We also propose a GMM-based estimate of the speed of learning.
In this article, we consider the possibility that some liquidity traders preannounce the size of their orders, a practice
that has come to be known as “sunshine trading”. Two possible effects preannouncement might have on the equilibrium are examined.
First, since it identifies certain trades as informationless, preannouncement changes the nature of any informational asymmetries
in the market. Second, preannouncement can coordinate the supply and demand of liquidity in the market. We show that preannouncement
typically reduces the trading costs of those who preannounce, but its effects on the trading costs and welfare of other traders
are ambiguous. We also examine the implications of preannouncement for the distribution of prices and the amount of information
that prices reveal.
We examine the effects of trading after hours on the amount and timing of price discovery over the 24-hour day. A high volume
of liquidity trade facilitates price discovery. Thus prices are more efficient and more information is revealed per hour during
the trading day than after hours. However, the low trading volume after hours generates significant, albeit inefficient, price
discovery. Individual trades contain more information after hours than during the day. Because information asymmetry declines
over the day, price changes are larger, reflect more private information, and are less noisy before the open than after the
close.
Patterns in stock market trading volume, trading costs, and return volatility are examined using New York Stock Excha nge data from 1988. Intraday test results indicate that, for actively traded firms trading volume, adverse selection costs, and return volatility are higher in the first half-hour of the day. This eviden ce is inconsistent with the Admati and Pfleiderer (1988) model which predicts that trading costs are low when volume and return volatilit y are high. Interday test results show that, for actively traded firms , trading volume is low and adverse selection costs are high on Monday , which is consistent with the predictions of the Foster and Viswanath an (1990) model. Copyright 1993 by American Finance Association.
The behavior of time-weighted bid-ask spreads over the trading day are examined. The plot of minute-by-minute spreads versus time of day has a crude reverse J-shaped pattern. Schwartz identifies four determinants of spreads: activity, risk, information, and competition. Using a linear regression model, a significant relationship between these same factors and intraday spreads is demonstrated, but dummy variables for time of day have a reverse J-shape. For given values of the activity, risk, information, and competition measures, spreads are higher at the beginning and end of the day relative to the interior period. Copyright 1992 by American Finance Association.
A dynamic model of insider trading with sequential auctions, structured to resemble a sequential equilibrium, is used to examine the informational content of prices, the liquidity characteristics of a speculative market, and the value of private information to an insider. The model has three kinds of traders: a single risk neutral insider, random noise traders, and competitive risk neutral market makers. The insider makes positive profits by exploiting his monopoly power optimally in a dynamic context, where noise trading provides camouflage which conceals his trading from market makers. As the time interval between auctions goes to zero, a limiting model of continuous trading is obtained. In this equilibrium, prices follow Brownian motion, the depth of the market is constant over time, and all private information is incorporated into prices by the end of trading.
This paper analyzes price formation under two trading mechanisms: a continuous quote-driven system where dealers post prices before order submission and an order-driven system where traders submit orders before prices are determined. The order-driven system operates either as a continuous auction, with immediate order execution, or as a periodic auction, where orders are stored for simultaneous execution. With free entry into market making, the continuous systems are equivalent. While a periodic auction offers greater price efficiency and can function where continuous mechanisms fail, traders must sacrifice continuity and bear higher information costs. Copyright 1992 by American Finance Association.
This paper examines the effects of the mechanism by which securities are traded on their price behavior. We compare the behavior of open‐to‐open and close‐to‐close returns on NYSE stocks, given the differences in execution methods applied in the opening and closing transactions. Opening returns are found to exhibit greater dispersion, greater deviations from normality and a more negative and significant autocorrelation pattern than closing returns. We study the effects of the bid‐ask spread and the price‐adjustment process on the estimated return variances and covariances and discuss the associated biases. We conclude that the trading mechanism has a significant effect on stock price behavior.
Automated versus floor trading: An analysis of execution costs on the Paris and New York exchanges
- K Venkataraman
A call auction's impact on price formation and order routing: Evidence from the NASDAQ stock market
- M S Pagano
Lifting the veil: An analysis of pre-trade transparency at the NYSE
- E Boehmer
The high-frequency trading arms race: Frequent batch auctions as a market design response
- E Budish
The effect of a closing call auction on market quality and trading strategies
- E Kandel
Working remotely and the supply-side impact of Covid-19. Unpublished working paper
- D Papanikolaou