Optimal market making in the presence of latency

This paper studies optimal market making for large-tick assets in the presence of latency. We consider a random walk model for the asset price and formulate the market maker's optimization problem using Markov Decision Processes (MDP). We characterize the value of an order and show that it plays the role of one-period reward in the MDP model. Based on this characterization, we provide explicit criteria for assessing the profitability of market making when there is latency. Under our model, we show that a market maker can earn a positive expected profit if there are sufficient uninformed market orders hitting the market maker's limit orders compared with the rate of price jumps, and the trading horizon is sufficiently long. In addition, our theoretical and numerical results suggest that latency can be an additional source of risk and latency impacts negatively the performance of market makers.     

CORRELATED BEHAVIOR IN LIMIT ORDER CANCELLATIONS,COMOVEMENT IN ASSET RETURNS,AND COMMONALITY IN LIQUIDITY

We examine whether there is common behavior in limit order cancellation activity, that is, commonality in cancellation activity, on U.S. exchanges. We then examine whether this commonality in cancellation activity is associated with increased levels of return comovement and commonality in liquidity. We document strong evidence of limit order traders exhibiting exchange, industry, marketwide, and stock-level commonality with regard to cancellation activity, which is consistent with limit order traders exhibiting correlated trading behavior. We also find that this correlated behavior in cancellation activity is associated with increased levels of return comovement and commonality in liquidity.     

Estimating the Gains from Trade in Limit-Order Markets

We present a method to estimate the gains from trade in limit‐order markets and provide empirical evidence that the limit‐order market is a good market design. Using observations on order submissions and execution and cancellation histories, we estimate both the distribution of traders' unobserved valuations for the stock and latent trader arrival rates. We use the resulting estimates to compute the current gains from trade, the gains from trade in a perfectly liquid market, and the gains from trade with a monopoly liquidity supplier. The current gains are 90% of the maximum gains and 150% of the monopolist gains.     

Price formation,market quality and the effects of reduced latency in the very short run

Applying an innovative event study methodology to ultra short return horizons, this paper resolves market adjustment in the aftermath of corporate news events with unprecedented precision. It uncovers the ramifications of the reduction in latency of the German stock market on April 23rd 2007 and shows that it has had positive consequences for market quality. Analyzing second by second time windows the paper demonstrates that price determination, market efficiency as well as quoted spreads and order flow have significantly improved not only in broad average terms, but in particular during informative events.     

The diversity of high-frequency traders

The regulatory debate concerning high-frequency trading (HFT) emphasizes the importance of distinguishing different HFT strategies and their influence on market quality. Using data from NASDAQ-OMX Stockholm, we compare market-making HFTs to opportunistic HFTs. We find that market makers constitute the lion's share of HFT trading volume (63–72%) and limit order traffic (81–86%). Furthermore, market makers have higher order-to-trade ratios and lower latency than opportunistic HFTs. In a natural experiment based on tick size changes, we find that the activity of market-making HFTs mitigates intraday price volatility.     

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.     

Trading and Ordering Patterns of Market Participants in High Frequency Trading Environment: Empirical Study in the Japanese Stock Market

In this study, we investigate ordering patterns of different types of market participants in Tokyo Stock Exchange (TSE) by examining order records of the listed stocks. Firstly, we categorize the virtual servers in the trading system of TSE, each of which is linked to a single trading participant, by the ratio of cancellation and execution in the order placement as well as the number of executions at the opening of the afternoon session. Then, we analyze ordering patterns of the servers in the categories in short intervals for the top 10 highest trading volume stocks. By classifying the intervals into four cases by returns, we observe how different types of market participants submit or execute orders in the market situations. Moreover, we investigate the shares of the executed volumes for the different types of servers in the swings and roundabouts of the Nikkei 225 index, which were observed in September in 2015. The main findings of this study are as follows: Server type A, which supposedly includes non-market making proprietary traders with high-speed algorithmic strategies, executes and places orders along with the direction of the market. The shares of the execution and order volumes along with the market direction increase when the stock price moves sharply. Server type B, which presumably includes servers employing a market making strategy with high cancellation and low execution ratio, shifts its market making price ranges in the rapid price movements. We observe that passive servers in Server type B have a large share and buy at low levels in the price falls. Also, Server type B, as well as Server type A, makes profit in the price falling days and particularly, the aggressive servers in the server type make most of the profit. Server type C, which is assumed to include servers receiving orders from small investors, constantly has a large share of execution and order volume.     

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.     

订单型操纵的新发展及监管

本文考察了一类新的操纵类型——订单型操纵及其监管。研究发现,对于订单型操纵而言,订单提交频率较高且撤单速度非常快,以避免成交风险;申报买入笔数很多且提交订单额度巨大,但成交笔数极少;买入申报撤单量占该股票当日市场买入总申报比例极高。进一步,操纵者选择的股票往往具有低股价和小市值的特征;操纵行为对价格和流动性仅有短暂的影响。比较发现,中国和美国订单型操纵在制度上存在差异。本文研究对于如何在中国更好地加强这一类新型操纵的监管有着借鉴意义。     

Quote-based competition,market share,and execution quality in NASDAQ-listed securities

We show that competitive quotes help increase dealer market share on NASDAQ, despite the fact that a large proportion of order flow is preferenced. We find that decimal pricing and the introduction of new trading platforms such as SuperSOES and SuperMontage have significantly changed the effect of quote aggressiveness on dealer market share. In particular, decimal pricing reduces (increases) the price (size) elasticity, SuperSOES increases the size elasticity, and SuperMontage increases both the size and price elasticity of dealer market share. We also show that market centers provide greater price improvements and faster executions when they post competitive quotes.     

Regulation NMS and Market Quality

We show that both the quoted and effective spreads increased, the quoted depth decreased, and the market quality index decreased after the implementation of Regulation National Market System (NMS) (Reg NMS). We also find an increase in the price impact of trades and the dispersion of the pricing error after Reg NMS. The order execution speed is slower, the order fill rate is lower, and the order cancellation rate is higher for most trades after Reg NMS. Hence, contrary to the Securities and Exchange Commission's belief, Reg NMS has proven to be detrimental to most traders. NASDAQ provided faster and more reliable executions than the NYSE/AMEX, and NASDAQ gained market shares from the NYSE/AMEX and other trading venues after Reg NMS.     

Human vs. high-frequency traders,penny jumping,and tick size

This paper examines changes in market quality resulting from the smaller tick size of the interbank foreign exchange market. Coupled with the lower tick size, the special composition of traders and their order placement strategies created a suitable environment for high-frequency traders (HFT’s) to implement sub-penny jumping strategy to front-run human traders. We show that the spread declined following the introduction of decimal pip pricing. However, benefits of spread reduction were mostly absorbed by the HFT’s. Market depths were also significantly reduced with the occupation of the top of the order book by HFT’s. This new environment changed the market maker-market taker composition between different traders and altered price impacts of the order flows.     

High frequency trading and end-of-day price dislocation

We show that the presence of high frequency trading (HFT) has significantly mitigated the frequency and severity of end-of-day price dislocation. The effect of HFT is more pronounced on days when end of day price dislocation is more likely to be the result of market manipulation. Moreover, the effect of HFT is more pronounced than the role of trading rules, surveillance, enforcement and legal conditions in curtailing the frequency and severity of end-of-day price dislocation. We show our findings are robust to different proxies of the start of HFT by trade size, cancellation of orders, and co-location.     

Market proxies as factors in linear asset pricing models: Still living with the roll critique

A new model misspecification measure for linear asset pricing models is proposed for the case where misspecification maps to latency of one of the pricing factors; in this case, the market return. This measure is suited both for testing models that include the market return as a pricing factor in a traditional sense (i.e., whether the chosen model does or does not price a collection of risky assets) and ranking those models (i.e., determining which model performs best). The proposed measure is used in pricing portfolios reflecting the size, value, and momentum premia. The conditional CAPM of Jagannathan and Wang (1996) is found to best the performance of both the simple CAPM and the ICAPM of Petkova (2006). Moreover, it is discovered that winner stocks in a momentum portfolio may have higher market betas than loser stocks.     

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.     

Liquidity distribution in the limit order book on the stock exchange of Thailand

The liquidity distribution, or the shape of the limit order book, influences trading behavior and choice of order submission by public liquidity suppliers. The present study seeks to discover whether liquidity providers are concerned about being picked off by informed traders, and whether they are less willing to supply liquidity at the market or demand higher price spreads. The results show that liquidity at the market is a small portion of total liquidity, and that firm size, minimum tick size, volatility, and trading volume play significant roles in determining the liquidity distribution within an order book.     

Hidden liquidity: An analysis of order exposure strategies in electronic stock markets

Many stock exchanges choose to reduce market transparency by allowing traders to hide some or all of their order size. We study the costs and benefits of order exposure and test hypotheses regarding hidden order usage using a sample of Euronext-Paris stocks, where hidden orders represent 44% of the sample order volume. Our results support the hypothesis that hidden orders are associated with a decreased probability of full execution and increased average time to completion, and fail to support the alternate hypothesis that order exposure causes defensive traders to withdraw from the market. However, exposing rather than hiding order size increases average execution costs. We assess the extent to which non-displayed size is truly hidden and document that the presence and magnitude of hidden orders can be predicted to a significant, but imperfect, degree based on observable order attributes, firm characteristics, and market conditions. Overall, the results indicate that the option to hide order size is valuable, in particular, to patient traders.     

Increasing the Tick: Examining the Impact of the Tick Size Change on Maker‐Taker and Taker‐Maker Market Models

We investigate the effects of an increase in tick size on order and trading flow across market fee models. Using the pilot firms in the U.S. Securities and Exchange Commission's Tick Size Pilot Program, we document that trade and order volume declines on maker‐taker fee models after the tick size implementation. We find that the inverted fee models (taker‐maker) experience an increase in both trade and order volume. Additionally, we find that a tick size adjustment has a substantial influence on market participation in maker‐taker fee models. We also find that measures of both hidden and algorithmic trading decline with an increasing tick size, which is strongly moderated by the differences in the maker‐taker and taker‐maker fee models.     

Order price clustering,size clustering,and stock price movements: Evidence from the Taiwan Stock Exchange

This paper examines order price clustering, size clustering, and stock price movements in an active emerging country’s equities market, the Taiwan Stock Exchange (TWSE). We first explore the relationships between investor types and order price/size clustering. Next, we investigate the joint determinants of the round-price and round-size orders based on daily and intraday data analyses. Finally, we look at the relationships among investor types, round prices/sizes, and stock price movements. The findings reveal that all investor types exhibit price and size clustering phenomena. After controlling for other factors, institutional investors have a relatively lower level of size clustering when compared with individuals. Our results confirm the price resolution hypothesis, whereby the levels of daily price and size clustering increase with firm risk, and the probability of a round-price or round-size order increases as transitory volatility rises. Partially consistent with the negotiation hypothesis, the probability of a round-price or round-size order increases when order competition turns fiercer. Mutual funds exhibit stronger quarter-end and session-end effects than do other investors. We also detect strategic trading behaviors, showing that the probability of an order with a tail price of one (nine) increases when buy (sell) order competition is fiercer. Lastly, stocks with mutual funds’ round-price or round-size buy (sell) orders experience rising (falling) future stock returns.     

Portfolio Returns,Market Volatility,and Seasonality

This paper examines three important issues related to the relationship between stock returns and volatility. First, are Duffee's (1995) findings of the relationship between individual stock returns and volatility valid at the portfolio level? Second, is there a seasonality of the market return volatility? Lastly, do size portfolio returns react symmetrically to the market volatility during business cycles? We find that the market volatility exhibits strong autocorrelation and small size portfolio returns exhibit seasonality. However, this phenomenon is not present in large size portfolios. For the entire sample period of 1962–1995, the highest average monthly volatility occurred in October, followed by November, and then January. Examining the two sub-sample periods, we find that the average market volatility increases by 15.4% in the second sample period of 1980–1995 compared to the first sample period of 1962–1979. During the contraction period, the average market volatility is 60.9% higher than that during the expansion period. Using a binary regression model, we find that size portfolio returns react asymmetrically with the market volatility during business cycles. This paper documents a strongly negative contemporaneous relationship between the size portfolio returns and the market volatility that is consistent with the previous findings at the aggregate level, but is inconsistent with the findings at the individual firm level. In contrast with the previous findings, however, we find an ambiguous relationship between the percentage change in the market volatility and the contemporaneous stock portfolio returns. This ambiguity is attributed to strongly negative contemporaneous and one-month ahead relationships between the market volatility and portfolio returns.