An Examination of Changes in Specialists' Posted Price Schedules

New York Stock Exchange specialists disseminate informationto market participants by displaying price schedules consistingof bid prices, ask prices, bid depths, and ask depths. We examinehow specialists update these price schedules in a simultaneousequations model. We find that changes in the best prices anddepths on the limit order book have a significant impact onthe posted price schedule, while the effects of transactionsand order activity are secondary. Furthermore, we show thatspecialists revise prices and depths differently, but find noevidence that they revise the price schedule in response tochanges in inventory.     

Do aggressive orders affect liquidity? An evidence from an emerging market

This paper investigates how aggressive orders affect spreads and trading activity measures on the stock market. Based on a sample of stocks listed on the Warsaw Stock Exchange this study finds that spreads and trading activity measures increase significantly when aggressive orders are executed, but quickly revert to initial levels. The reaction to these orders on the bid and ask side of the market is similar. The effect of aggressive orders differ depending on the size of the firms. Trading activity measures such as volumes or number of transactions increase stronger for bigger than for smaller stocks, while spreads increase more for smaller firms than for bigger ones. These findings enrich the understanding of liquidity dynamics especially on the emerging markets where liquidity is an important price formation factor.     

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.     

Price Movement Effects on the State of the Electronic Limit‐Order Book

This paper investigates public‐trader order‐placement strategies by examining the relations between the state of the limit‐order book and previous price movements. There is support for an information effect, as traders become more aggressive in buying and more patient in selling after previous positive stock returns. The widening of the bid‐ask spread also causes traders to place less aggressive orders. However, there is no evidence of the options effect on limit‐order trading. This study also reveals that orders at the best quotes react faster and complete the adjustment earlier than orders that are far away from the best quotes.     

The impact of aggressive orders in an order-driven market: a simulation approach

This article investigates resiliency in an order-driven market. On basis of a vector autoregressive model capturing various dimensions of liquidity and their interactions, I simulate the effect of a large liquidity shock, measured by a very aggressive market order. I show that, despite the absence of market makers, the market is resilient. All dimensions of liquidity (spread, depth at the best prices and order book imbalances) revert to their steady-state values within 15 orders after the shock. For prices, a long run effect is found. Furthermore, different dimensions of liquidity interact. Immediately after a liquidity shock, the spread becomes wider than in the steady state, implying that one dimension of liquidity deteriorates, while at the same time, depth at the best prices increases, meaning an improvement of another liquidity dimension. In subsequent periods, the spread reverts back to the steady-state level but also depth decreases. Also, I find evidence for asymmetries in the impact of shocks on the ask and bid side. Shocks on the ask side have a stronger impact than shocks on the bid side. Finally, resiliency is higher for less-frequently traded stocks and stocks with a larger relative tick size.     

A note on price limit performance: The case of illiquid stocks

In the Chinese stock markets, there are A-shares and B-shares. Both share-types have identical cash flow rights but different ownership structures (i.e., A-shares are owned by local Chinese citizens and B-shares are owned primarily by foreigners), causing B-shares to be less liquid relative to A-shares. However, even though B-shares have much wider bid—ask spreads than A-shares, both share-types are subject to the same 10% daily price limit regulation. As such, B-shares, simply due to their wider spreads, may be more inclined than A-shares to hit price limits. Our empirical results support this contention. The findings have policy implications. First, given wide spreads for illiquid stocks, exchanges may consider using midpoint prices (between bid and ask prices) to establish price limit ranges for illiquid stocks. In addition, and perhaps more importantly, exchanges may consider using wider price limits for less liquid classes of stocks.     

Microstructure and reverse stock splits

In this paper we show that, similar to NYSE/AMEX stocks, NASDAQ stocks exhibit significant ex date returns for reverse stock splits. Although the 10-day cumulative return after the ex date is close to –10%, this does not violate market efficiency, because the average bid-ask spread for the reverse split stock is at least double this return. We also document that these large negative returns are mostly due to a drop in the ask price while bid prices barely change at all. Furthermore, the ex date returns are negatively related to trading volume.These results suggest that there is abnormal selling and a significant buildup of market makers' inventories near the ex date. To reduce the inventory buildup, market makers lower ask prices to induce buying by investors, resulting in the observed negative returns. Lowering bid prices, an alternative strategy for reducing inventories, is not attractive to market makers due to competitive factors and the reduction of commissions associated with a smaller number of transactions. Notably, selling investors have no incentives to sell their stocks early to avoid the observed negative ex date return, since this return is largely an ask price phenomenon and does not represent realized returns to sellers.     

Market-making costs in Treasury bills: A benchmark for the cost of liquidity

We focus on market-making costs by examining the daily bid–ask spreads for off-the-run, one-month Treasury bills around two liquidity-changing events. Event one, Salomon Brothers’ supply shock, results in a roughly 2.5-basis-point increase in the spread because of an increase in ask prices; and event two, the Long-Term Capital Management demand shock, results in a doubling of the spread because of a decrease in bid prices. Our results provide a benchmark for researchers examining bid–ask spreads of securities that include a liquidity premium, a risk premium, and an asymmetric information premium.     

Minimum Price Variations,Time Priority,and Quote Dynamics

We analyze price competition between dealers in a security market where the bidding process is sequential. The model provides an interpretation for the evolution of the best ask and bid prices, in between transactions. We find that convergence to the competitive ask and bid prices can take time. The speed of convergence is determined by the frequency with which dealers check their offers and by the tick size. This creates a relationship between the expected trading cost and the timing of offers posted by the dealers. We also find that a zero minimum price variation never minimizes the expected trading cost. Finally, we study the role of time priority. Journal of Economic Literature Classification Numbers: D43, G10.     

Order Arrival,Quote Behavior,and the Return-Generating Process

This paper establishes three empirical results. We find positive autocorrelation in actual intra-day stock returns, in intra-day returns computed from quote midpoints, and in the arrival of buy and sell orders. We present a model of return generation that incorporates these features via lagged adjustment of the limit-order price and positive dependence in bid and ask transactions. The return model is observationally equivalent to an ARMA process, which is consistent with the observed return behavior.     

Optimal high-frequency trading with limit and market orders

We propose a framework for studying optimal market-making policies in a limit order book (LOB). The bid–ask spread of the LOB is modeled by a tick-valued continuous-time Markov chain. We consider a small agent who continuously submits limit buy/sell orders at best bid/ask quotes, and may also set limit orders at best bid (resp. ask) plus (resp. minus) a tick for obtaining execution order priority, which is a crucial issue in high-frequency trading. The agent faces an execution risk since her limit orders are executed only when they meet counterpart market orders. She is also subject to inventory risk due to price volatility when holding the risky asset. The agent can then also choose to trade with market orders, and therefore obtain immediate execution, but at a less favorable price. The objective of the market maker is to maximize her expected utility from revenue over a short-term horizon by a trade-off between limit and market orders, while controlling her inventory position. This is formulated as a mixed regime switching regular/impulse control problem that we characterize in terms of a quasi-variational system by dynamic programming methods. Calibration procedures are derived for estimating the transition matrix and intensity parameters for the spread and for Cox processes modelling the execution of limit orders. We provide an explicit backward splitting scheme for solving the problem and show how it can be reduced to a system of simple equations involving only the inventory and spread variables. Several computational tests are performed both on simulated and real data, and illustrate the impact and profit when considering execution priority in limit orders and market orders.     

Information Disclosure and Stock Liquidity: Evidence from Borsa Italiana

This article examines the effect of increased corporate information disclosure on stock liquidity. Using the adoption of International Financial Reporting Standards (IFRS) in Italy as a natural experiment we extend previous work examining the effect on one measure of liquidity—bid‐ask spreads—to others, specifically depth and the price impact of transactions (or effective bid‐ask spreads). Consistent with previous research we find that bid‐ask spreads of stocks decline following the introduction of IFRS, which implies that stock liquidity increases for small traders. However, we also provide evidence that depth at the best quotes declines, which challenges the proposition that liquidity increases for large trades following an increase in disclosure. In additional tests, we find that effective bid‐ask spreads of block trades also decline following the introduction of IFRS. Overall, this evidence confirms that stock liquidity for both small and large trades increases following an increase in corporate information disclosure.     

Relative performance of bid–ask spread estimators: Futures market evidence

The issue of transaction costs is the mainstay of the equity market microstructure. Research in the microstructure of futures markets has lagged behind. A primary reason is that futures exchanges in the U.S. do not record bid–ask quotes, requiring these costs to be imputed from transaction price data. A reliable estimator of bid–ask spreads would significantly enhance microstructure research in futures markets. Unique intraday data from the Sydney Futures Exchange (SFE) that include both transaction prices and bid–ask spreads allow us to compare bid–ask spread estimation techniques proposed in the literature against the benchmark of actual spreads in a futures market, and thus identify the best-performing estimator. To maximize relevance, we impose all the constraints that apply in U.S. futures data to perform our estimations. We find that the four bid–ask spread estimators considered significantly underestimate the actual spreads. However, simple moments-based estimators perform better in predicting spreads.     

Central limit theorem for the realized volatility based on tick time sampling

A central limit theorem for the realized volatility estimator of the integrated volatility based on a specific random sampling scheme is proved, where prices are sampled with every ‘continued price change’ in bid or ask quotation data. The estimator is shown to be robust to market microstructure noise induced by price discreteness and bid–ask spreads. More general sampling schemes also are treated in case that the price process is a diffusion.     

Large option trades, market makers, and limit orders

This article focuses on the difference between market makersand limit orders in their role as suppliers of liquidity. Forboth sources of liquidity I analyze the price behavior of stocksand options around large option trades and I estimate the premiumpaid by the initiator of the large trade. My findings suggestthat limit orders for options are 'picked off' after adversechanges in the underlying stock price. Furthermore, I find thatfor these transactions there is a permanent change in quotationsin the direction of the transaction. After transactions wheremarket makers supply liquidity, quotes tend to return to theirpretrade level.     

Intraday futures market behaviour around major scheduled macroeconomic announcements: Australian evidence

This paper examines intraday futures market behaviour around major scheduled macroeconomic information announcements on the Sydney Futures Exchange (SFE). Prior literature analysing intraday price behaviour around announcements is extended to trading volume and quoted bid–ask spreads. The analysis of price volatility, trading volume and quoted bid–ask spreads indicates that the majority of adjustment to new information occurs rapidly, within 240 seconds of the scheduled time for major announcements, with some evidence of abnormal activity prior to announcements. Analysis of quoted bid–ask spreads suggests that they significantly widen in the 20 seconds prior to announcements and remain significantly wider for 30 seconds following announcements. The increase in quoted spreads is related to both expected and unexpected volatility, implying that market participants increase quoted spreads around information announcements as a consequence of adverse selection costs.     

Liquidity supply in electronic markets

We examine the supply of liquidity by proprietary trading desks and hedge funds (PTDH) versus mutual funds, index funds, and insurance companies (MII) across ten bid (ask) steps of the limit order book. We document that institutional investors simultaneously supply liquidity at multiple prices in the limit order book. We also find that PTDHs are more price aggressive liquidity suppliers than MIIs, consistent with hypothesized responses to observed changes in the cost and risk of non-execution. We investigate whether these findings are robust to fast versus slow markets, the volatility of daily returns, and aggregate depth relative to daily volume.     

Impacts of trades in an error-correction model of quote prices

In this paper we analyze and interpret the quote price dynamics of 100 NYSE stocks stratified by trade frequency. We specify an error-correction model for the log difference of the bid and the ask price with the spread acting as the error-correction term, and include as regressors the characteristics of the trades occurring between quote observations, if any. From this model we are also able to extract the implied model for the spread and the mid-quote. We find that short duration and medium volume trades have the largest impacts on quote prices for all one hundred stocks. Further, we find that buys have a greater impact on the ask price than on the bid price, while sells have a greater impact on the bid price than on the ask price. Both buys and sells increase spreads in the short run, but in the absence of further trades, the spreads mean revert. Trades have a greater impact on quotes for the infrequently traded stocks than for the more actively traded stocks.     

Stock splits in a retail dominant order driven market

This paper uses intraday and daily data from the Stock Exchange of Thailand (SET) between 2002 and 2004 to provide evidence that firms use stock splits to bring their stock prices down to a preferred trading range of their clientele base. Stock splits reduce bid–ask spreads and intraday and daily price impact while increasing depths supplied by retail investors who account for 60–70% of trading on the SET. Firms that choose a high split factor experience greater improvement in liquidity. The study finds no evidence that split announcements are used to signal post-split earnings performance.     

Estimating the profits from trading strategies

Price improvement is the difference between the execution priceof an order and the quoted bid or ask when the order was submitted.We show that expected price improvement falls off dramaticallyas the size of the order approaches the quoted depth, and becomesnegative for larger orders. This is particularly important forsmall firms because the quoted depths are low. Using quotedspreads and depths and our estimate of expected price improvement,we show that trading strategies that attempt to exploit theweekly predictability of small-firm returns would be swampedby transaction costs.