Specialist participation and limit orders

We present a market microstructure model to examine specialist's strategic participation decisions in a security market where there are noise traders, limit order traders, an insider and a specialist. We argue that the specialist's participation rate depends on the depth of the limit book and its uncertainty. In particular, the specialist has incentives to trade against the market trend when the limit book depth is low and to trade with the market trend when the depth is high. Moreover, the specialist's participation rate is positively related to the limit book depth uncertainty and the asset price volatility, but is negative related to the average trading volume. We also discuss the specialist's participation strategies under the NYSE regulation that prohibits the specialist from trading with the market trend.     

The impact of designated market makers on security prices

This paper is divided into two distinct parts. Part I, Empirical Evidence, tests a previously formulated variance, thinness relationship for security returns. First quarter 1972 daily returns variance is regressed on market value of shares, share price, trading activity, sales variance, and institutional holdings for 178 firms selected by stratified random sampling from AMEX and NYSE (specialist exchanges), and from Tokyo and Rio de Janeiro (non-specialist exchanges). The principal finding is that returns variance and market value are inversely related on non-specialist exchanges, but not on specialist exchanges; this difference is attributed to specialists' impact. Part II, Policy Proposals, discusses the manner in which designated market makers may be effectively incorporated into a continuous auction exchange. Issues discussed include: desirability of price stabilization, transfers implicit in the existing U.S. specialist system, consolidation and public availability of the limit order book, number of designated market makers for a security, competitive bidding, and compensation for performing the price stabilization function. Stabilization is modeled as an external economy, and specific policy proposals for internalizing it are advanced.     

Hybrid markets, tick size and investor trading costs

This paper shows how the tick size affects equilibrium outcomes in a hybrid stock market such as the NYSE that features both a specialist and a limit order book. Reducing the tick size facilitates the specialist's ability to step ahead of the limit order book, resulting in a reduction in the cumulative depth of the limit order book at prices above the minimum tick. If market demand is price-sensitive, and there are costs of limit order submission, the limit order book can be destroyed by tick sizes that are either too small or too large. We show that trading cost is minimized at larger tick sizes for larger market orders, creating an incentive to submit smaller orders when tick size is reduced. With a smaller tick size, specialist participation increases and specialist profit increases slightly for small market orders, and considerably for large market orders.     

Liquidity in auction and specialist market structures: Evidence from the Italian bourse

Several studies find that bid-ask spreads for stocks listed on the NYSE are lower than for stocks listed on NASDAQ. While this suggests that specialist market structures provide greater liquidity than competing dealer markets, the nature of trading on the NYSE, which comprises a specialist competing with limit order flow, obfuscates the comparison. In 2001, a structural change was implemented on the Italian Bourse. Many stocks that traded in an auction market switched to a specialist market, where the specialist controls order flow. Results confirm that liquidity is significantly improved when stocks commence trading in the specialist market. Analysis of the components of the bid-ask spread reveal that the adverse selection component of the spread is significantly reduced. This evidence suggests that specialist market structures provide greater liquidity to market participants.     

Price experimentation and security market structure

We examine the role of market makers in facilitating price discovery.We show that a specialist may experiment with prices to inducemore informative order flow. thereby expediting price discovery.Market makers in a multiple-dealer system, unlike a specialistsystem, do not have the incentives to perform such costly experimentsbecause of free-rider problems. Consequently, the specialistsystem may provide open markets where competition fails butat the cost of wider bid-ask spreads. We analyze the effectof experimentation on the bid-ask spread and provide an exploratoryanalysis of intraday specialist data that is consistent withour price experimentation hypothesis.     

The strategic specialist and imperfect competition in a limit order market

The empirical literature suggests that the limit order book contains information that might be used by the specialist to his own advantage. I develop a model where there is a strategic specialist who competes against a limit order book and has information about supply. The presence of a strategic specialist in an imperfectly competitive limit order book market induces non-monotonicity of market indicators with respect to the variance of liquidation value. Moreover, the existence of private information about supply significantly affects market performance as it induces, among other effects, lower market liquidity. Finally, this model suggests another link between Kyle’s (1985, 1989) [Kyle, A., 1985. Continuous auctions and insider trading. Econometrica 53, 1315–1336, Kyle, A., 1989. Informed speculators with imperfect competition. Review of Economic Studies 56, 317–356] and Glosten and Milgrom’s (1985) [Glosten, L., Milgrom, P., 1985. Bid, ask and transaction prices in a specialist market with heterogeneously informed markets. Journal of Financial Economics 14, 71–100] models by allowing for strategic behaviour of the specialist.     

Splitting orders

A standard presumption of market microstructure models is thatcompetition between risk-neutral market makers inevitably leadsto price schedules that leave market makers zero expected profitsconditional on the order flow. This article documents an importantlack of robustness of this zero-profit result. In particular,we show that if traders can split orders between market makers,then market makers set less-competitive price schedules thatearn them strictly positive profits and hence raise tradingcosts. Thus, this article can explain why somebody might willinglymake a market for a stock when there are fixed costs to doingso. The analysis extends to a limit order book, which by itsnature is split against incoming market orders: equilibriumlimit order schedules necessarily yield those agents positiveexpected profits.     

Liquidity,volume and price efficiency: The impact of order vs. quote driven trading

As equity trading becomes predominantly electronic, is there still value to a traditional, intermediated dealer system? We address this question by comparing the impact of the organization of trading on volume, liquidity, and price efficiency in a quote-driven dealer market and in an order-driven limit order book. Small order price impacts are higher and large order price impacts are lower in a dealer market. Prices are more efficient in the limit order book, except when the level of informed trading is high. Volume is higher in a limit order market, making this system most attractive for trading venues.     

Liquidity provision with limit orders and a strategic specialist

This article presents a microstructure model of liquidity provisionin which a specialist with market power competes against a competitivelimit order book. General solutions, comparative statics andexamples are provided first with un-informative orders and thenwhen order flows are informative. The model is also used toaddress two optimal market design issues. The first is the effectof 'tick' size - for example, eighths versus decimal pricing- on market liquidity. Institutions trading large blocks havea larger optimal tick size than small retail investors, butboth prefer a tick size strictly greater than zero. Second,a hybrid specialist/limit order market (like the NYSE) providesbetter liquidity to small retail and institutional trades, buta pure limit order market (like the Paris Bourse) may offerbetter liquidity on mid-size orders.     

Related securities and price discovery: Evidence from NYSE-listed Non-U.S. stocks

In this paper we analyze whether handling related securities improves a market maker's information environment and helps to incorporate new information in stock prices. Our empirical tests are focused on New York Stock Exchange specialists and the U.S. share in price discovery of 64 British and French companies cross-listed on the NYSE. We define related securities as stocks from the same country, the same region, or other foreign stocks. We find strong evidence that a higher prominence of related stocks in the specialist portfolio is associated with a higher U.S. share in price discovery of our sample firms. We interpret our findings as evidence that concentrating market makers in similar stocks reduces information asymmetries and improves the information environment as market makers can extract information relevant to a stock from order flow to related securities. To support our argument, we show that the adverse selection component of the bid–ask spread is negatively related to the prominence of other foreign stocks in the specialist portfolio.     

Market or limit orders?

In this paper we investigate the problem of optimal order placement of an asset listed on an exchange using both market and limit orders in a simple model of market dynamics. We seek to understand under which settings it is optimal to place limit or market orders. Limit orders typically lower transaction costs but increase the risk of incomplete order execution, whereas market orders typically have higher transaction costs but are guaranteed to be executed. Rather than considering order book dynamics to determine if a limit order is executed we rely on price dynamics for this. We look at implementation shortfall in this setup with market impact of trading and propose a dynamic program to find the optimal placement of both market and limit orders for risk-neutral and risk-averse traders. With this we find a bound on the expected cost of trading and show that a trader who behaves optimally should always expect to pay less to trade less. We then solve the dynamic program numerically and examine optimal order placement strategies. We find that the decision between market and limit orders is sensitive to price volatility, risk aversion, and trading costs.     

Liquidity-Based Competition for Order Flow

We present a microstructure model of competition for order flowbetween exchanges based on liquidity provision. We find thatneither a pure limit order market (PLM) nor a hybrid specialist/limitorder market (HM) structure is competition-proof. A PLM canalways be supported in equilibrium as the dominant market (i.e.,where the hybrid limit book is empty), but an HM can also besupported, for some market parameterizations, as the dominantmarket. We also show the possible coexistence of competing markets.Order preferencing—that is, decisions about where ordersare routed when investors are indifferent—is a key determinantof market viability. Welfare comparisons show that competitionbetween exchanges can increase as well as reduce the cost ofliquidity.     

Limit Order Trading

We analyze the rationale for limit order trading. Use of limit orders involves two risks: 1) an adverse information event can trigger an undesirable execution, and 2) favorable news can result in a desirable execution not being obtained. On the other hand, a paucity of limit orders can result in accentuated short-term price fluctuations that compensate a limit order trader. Our empirical tests suggest that trading via limit orders dominates trading via market orders for market participants with relatively well balanced portfolios, and that placing a network of buy and sell limit orders as a pure trading strategy is profitable.     

交易限制与股票市场定价效率——基于创业板涨跌幅限制放宽的准自然实验研究

本文基于2020年8月24日创业板涨跌幅限制由10%扩大到20%这一政策变化建立准自然实验,从市场层面与公司事件层面探讨交易限制放宽的外生冲击下市场定价效率的变化。研究发现,涨跌幅限制放宽政策实施后,股票价格能更灵敏地反映公开市场信息,更多地包含公司层面特质信息,整体市场定价效率显著提升。进一步研究表明,涨跌幅限制放宽有效缓解了交易干扰问题,避免了过度交易行为延后,缓解了波动性外溢与价格发现延迟。异质性分析表明,无论是市场层面定价效率改善,还是事件层面波动性外溢、价格发现推迟与交易干扰问题的缓解,均在低信息透明度公司中更为显著。本文研究发现为验证涨跌幅限制会抑制股票市场定价效率的理论提供了直接经验证据,同时为推广完善市场化交易制度提供了有益启示。     

A market-clearing role for inefficiency on a limit order book

Limit order markets with stationary dynamics attract equal volumes of market orders and uncanceled limit orders, equalizing the supply and demand for liquidity and immediacy. To maintain this balance, market orders must share any benefit obtained by limit order traders from more efficient trading conditions, such as better order queuing policies. Therefore an efficient market places a low price on immediacy, producing small bid–ask spreads. Furthermore, when price-discreteness leads to a mainly constant spread, cutting the price tick raises surplus. This is modeled with a stochastic sequential game, using stationarity considerations to bypass direct analysis of traders’ intricate market forecasts.     

Myopic loss aversion and margin of safety: the risk of value investing

Abstract

Most modern financial markets use a continuous double auction mechanism to store and match orders and facilitate trading. In this paper we develop a microscopic dynamical statistical model for the continuous double auction under the assumption of IID random order flow, and analyse it using simulation, dimensional analysis, and theoretical tools based on mean field approximations. The model makes testable predictions for basic properties of markets, such as price volatility, the depth of stored supply and demand versus price, the bid–ask spread, the price impact function, and the time and probability of filling orders. These predictions are based on properties of order flow and the limit order book, such as share volume of market and limit orders, cancellations, typical order size, and tick size. Because these quantities can all be measured directly there are no free parameters. We show that the order size, which can be cast as a non-dimensional granularity parameter, is in most cases a more significant determinant of market behaviour than tick size. We also provide an explanation for the observed highly concave nature of the price impact function. On a broader level, this work suggests how stochastic models based on zero intelligence agents may be useful to probe the structure of market institutions. Like the model of perfect rationality, a stochastic zero intelligence model can be used to make strong predictions based on a compact set of assumptions, even if these assumptions are not fully believable.     

Price limit performance: evidence from transactions data and the limit order book

In recent years, organized stock exchanges with daily price limits adopted wider limits as narrower limits were criticized for jeopardizing market efficiency. This study examines the impact of a wide price limit on price discovery processes, using data from the Kuala Lumpur Stock Exchange. Specifically, examined is the impact of daily price limits on (i) information asymmetry; (ii) arrival rates of informed traders; and (iii) order imbalance. Using both trade-to-trade transaction data and the limit order book, we compile evidence that price limits do not improve information asymmetry, delays the arrival of informed traders, and exacerbates order imbalance. These results suggest that price limits on individual securities do not improve price discovery processes but impose serious costs even when the limit band is as wide as 30%.     

Second order approximations for limit order books

In this paper, we derive a second order approximation for an infinite-dimensional limit order book model, in which the dynamics of the incoming order flow is allowed to depend on the current market price as well as on a volume indicator (e.g. the volume standing at the top of the book). We study the fluctuations of the price and volume process relative to their first order approximation given in ODE–PDE form under two different scaling regimes. In the first case, we suppose that price changes are really rare, yielding a constant first order approximation for the price. This leads to a measure-valued SDE driven by an infinite-dimensional Brownian motion in the second order approximation of the volume process. In the second case, we use a slower rescaling rate, which leads to a non-degenerate first order approximation and gives a PDE with random coefficients in the second order approximation for the volume process. Our results can be used to derive confidence intervals for models of optimal portfolio liquidation under market impact.     

Implied Lévy volatility

We study the cause of large fluctuations in prices on the London Stock Exchange. This is done at the microscopic level of individual events, where an event is the placement or cancellation of an order to buy or sell. We show that price fluctuations caused by individual market orders are essentially independent of the volume of orders. Instead, large price fluctuations are driven by liquidity fluctuations, variations in the market's ability to absorb new orders. Even for the most liquid stocks there can be substantial gaps in the order book, corresponding to a block of adjacent price levels containing no quotes. When such a gap exists next to the best price, a new order can remove the best quote, triggering a large midpoint price change. Thus, the distribution of large price changes merely reflects the distribution of gaps in the limit order book. This is a finite size effect, caused by the granularity of order flow: in a market where participants place many small orders uniformly across prices, such large price fluctuations would not happen. We show that this also explains price fluctuations on longer timescales. In addition, we present results suggesting that the risk profile varies from stock to stock, and is not universal: lightly traded stocks tend to have more extreme risks.     

Limit Order Book as a Market for Liquidity

We develop a dynamic model of a limit order market populatedby strategic liquidity traders of varying impatience. In equilibrium,patient traders tend to submit limit orders, whereas impatienttraders submit market orders. Two variables are the key determinantsof the limit order book dynamics in equilibrium: the proportionof patient traders and the order arrival rate. We offer severaltestable implications for various market quality measures suchas spread, trading frequency, market resiliency, and time toexecution for limit orders. Finally, we show the effect of imposinga minimal price variation on these measures.