Competition for Order Flow and Smart Order Routing Systems

We study the rivalry between Euronext and the London Stock Exchange (LSE) in the Dutch stock market to test hypotheses about the effect of market fragmentation. As predicted by our theory, the consolidated limit order book is deeper after entry of the LSE. Moreover, cross‐sectionally, we find that a higher trade‐through rate in the entrant market coincides with less liquidity supply in this market. These findings imply that (i) fragmentation of order flow can enhance liquidity supply and (ii) protecting limit orders against trade‐throughs is important.     

Payments for Order Flow on Nasdaq

We present a model of Nasdaq that includes the two ways in which marketmakers compete for order flow: quotes and direct payments. Brokers in our model can execute small trades through a computerized system, preferencing arrangements with marketmakers, or vertical integration into market making. The comparative statics in our model differ from those of the traditional model of dealer markets, which does not capture important institutional features of Nasdaq. We also show that the empirical evidence is inconsistent with the traditional model, which suggests that preferencing and vertical integration are important components in understanding Nasdaq.     

LAPM: A Liquidity-Based Asset Pricing Model

The intertemporal CAPM predicts that an asset's price is equal to the expectation of the product of the asset's payoff and a representative consumer's intertemporal marginal rate of substitution. This paper develops an alternative approach to asset pricing based on corporations' desire to hoard liquidity. Our corporate finance approach suggests new determinants of asset prices such as the distribution of wealth within the corporate sector and between the corporate sector and the consumers. Also, leverage ratios, capital adequacy requirements, and the composition of savings affect the corporate demand for liquid assets and, thereby, interest rates.     

Competing for Order Flow in OTC Markets

We develop a model of a two‐sided asset market in which trades are intermediated by dealers and are bilateral. Dealers compete to attract order flow by posting the terms at which they execute trades—which can include prices, quantities, and execution speed—and investors direct their orders toward dealers who offer the most attractive terms. We characterize the equilibrium in a general setting, and we illustrate theoretically and numerically how the model can account for several important trading patterns in over‐the‐counter markets, which do not emerge from existing models.     

A Liquidity-Based Theory of Closed-End Funds

This paper develops a rational, liquidity-based model of closed-endfunds (CEFs) that provides an economic motivation for the existenceof this organizational form: They offer a means for investorsto buy illiquid securities, without facing the potential costsassociated with direct trading and without the externalitiesimposed by an open-end fund structure. Our theory predicts thepatterns observed in CEF initial public offerings (IPOs) andthe observed behavior of the CEF discount, which results froma trade-off between the liquidity benefits of investing in theCEF and the fees charged by the fund's managers. In particular,the model explains why IPOs occur in waves in certain sectorsat a time, why funds are issued at a premium to net asset value(NAV), and why they later usually trade at a discount. We alsoconduct an empirical investigation, which, overall, providesmore support for a liquidity-based model than for an alternativesentiment-based explanation.     

Competition For Order Flow, Market Quality, And Price Discovery In The Nasdaq 100 Index Tracking Stock

We investigate competition for order flow, market quality, and price discovery in the Nasdaq 100 Index Tracking Stock (QQQ). The QQQ, an AMEX‐listed, exchange‐traded fund, is the most actively traded security in the U.S. equities market. On July 31, 2001, the NYSE began trading the QQQ, marking the first time it traded securities of companies it does not list. The greatest volume of trading takes place on electronic communication networks (ECNs), following by trading on the AMEX and the NYSE. Most of the block trades are executed on the AMEX, where the bid‐ask spreads are narrower. We find that ECNs contribute the most to the price‐discovery process. The spreads on all trading platforms have decreased and market quality and price discovery have improved since QQQ shares have traded on the NYSE.     

Order Flow and Expected Option Returns

I show that the inventory risk faced by market‐makers has a first‐order effect on option prices. I introduce a simple approach that decomposes the price impact of trades into inventory risk and asymmetric information components. While both components are large for option trades, the inventory risk component is larger. Using the full panel of daily option returns, I find that option order imbalances attributable to inventory risk have five times larger impact on option prices than previously thought. Finally, I find that past order imbalances have greater predictive power than any other commonly used predictor of option returns.     

A Liquidity-Based Resolution of the Uncovered Interest Parity Puzzle

A new monetary theory is set out to resolve the “uncovered interest parity (UIP)” puzzle. It explores the possibility that liquidity properties of money and nominal bonds can account for the puzzle. A key concept in our model is that nominal bonds carry liquidity premia. We show that the UIP can fail to hold under the economic environment where collateral pledgeability and/or liquidity of nominal bonds and/or collateralized credit-based transactions are relatively bigger. Our liquidity-based theory can help understanding many empirical observations that risk-based explanations find difficult to reconcile with.     

Order Flow and Liquidity around NYSE Trading Halts

We study order flow and liquidity around NYSE trading halts. We find that market and limit order submissions and cancellations increase significantly during trading halts, that a large proportion of the limit order book at the reopen is composed of orders submitted during the halt, and that the market-clearing price at the reopen is a good predictor of future prices. Depth near the quotes is unusually low around trading halts, though specialists and/or floor traders appear to provide additional liquidity at these times. Finally, specialists appear to 'spread the quote' prior to imbalance halts to convey information to market participants.     

Intraday Patterns in FX Returns and Order Flow

Using a comprehensive high‐frequency foreign exchange data set, we present evidence of time‐of‐day effects in foreign exchange returns through a significant tendency for currencies to depreciate during local trading hours. We confirm this pattern across a range of currencies and time zones. We also find that this pattern is reflected in order flow and suggest that both patterns relate to the tendency of market participants to be net purchasers of foreign exchange in their own trading hours. Data from a single market maker appears to corroborate that interpretation.     

Quotes,Order Flow,and Price Discovery

The goal of this article is to examine the impact of 1975 Congressional mandate to integrate the trading of NYSE-listed stocks. The conclusions are: most of the time, the New York Stock Exchange (NYSE) quote matches or determines the best displayed quote, and the NYSE is the most frequent initiator of quote changes. Non-NYSE markets attract a significant portion of their volume when they are posting inferior bids or offers, indicating they obtain order flow for other reasons, such as “payment for order flow.” Yet, when a non-NYSE market does post a better bid or offer, it does attract additional order flow.     

Informed and Strategic Order Flow in the Bond Markets

We study the role played by private and public information inthe process of price formation in the U.S. Treasury bond market.To guide our analysis, we develop a parsimonious model of speculativetrading in the presence of two realistic market frictions—informationheterogeneity and imperfect competition among informed traders—anda public signal. We test its equilibrium implications by analyzingthe response of two-year, five-year, and ten-year U.S. bondyields to order flow and real-time U.S. macroeconomic news.We find strong evidence of informational effects in the U.S.Treasury bond market: unanticipated order flow has a significantand permanent impact on daily bond yield changes during bothannouncement and nonannouncement days. Our analysis furthershows that, consistent with our stylized model, the contemporaneouscorrelation between order flow and yield changes is higher whenthe dispersion of beliefs among market participants is highand public announcements are noisy.     

指令流:外汇市场研究的重要变量

外汇指令流的引入使市场微观结构理论成为近10年来汇率理论发展的一大亮点.令人惊奇的是,外汇指令流不仅在汇率波动和汇率决定研究中非常重要,而且许多传统争议因引进该变量而再次引发经济学家的兴趣,本文致力于介绍西方学术界对该理论的最新运用.     

Brokers and Order Flow Leakage: Evidence from Fire Sales

Using trade‐level data, we study whether brokers play a role in spreading order flow information in the stock market. We focus on large portfolio liquidations that result in temporary price drops, and identify the brokers who intermediate these trades. These brokers’ clients are more likely to predate on the liquidating funds than to provide liquidity. Predation leads to profits of about 25 basis points over 10 days and increases the liquidation costs of the distressed fund by 40%. This evidence suggests a role of information leakage in exacerbating fire sales.     

The Relationship Among Market-Making Revenue, Payment for Order Flow, and Trading Costs for Market Orders

We study the division of market-making revenue among dealer, broker, and trader. When Knight Securities, a major Nasdaq dealer, interacts with market orders in actively traded stocks during the fourth quarter of 1996, we estimate that its revenue is $0.057 per share. Knight pays brokers at least $0.025 per share (44% of revenue) for orders. To examine whether brokers appear to share these payments with traders, we compare net trading costs (trade price net of commissions) for traders using brokers routing Knight orders with estimated net trading costs for traders using the only discount broker we can determine did not directly receive market-making revenue. We find that the net trading cost of the broker refusing order-flow payments does not dominate the net trading cost of all brokers selling order flow to Knight. This finding suggests that order-flow payments do not unambiguously harm traders and challenges the conclusions of extant studies using only trade prices to assess market quality.     

Carry Trades,Order Flow,and the Forward Bias Puzzle

We investigate the relation between foreign exchange (FX) order flow and the forward bias. We outline a decomposition of the forward bias according to which a negative correlation between interest rate differentials and order flow creates a time‐varying risk premium consistent with that bias. Using 10 years of data on FX order flow, we find that more than half of the forward bias is accounted for by order flow—with the rest being explained by expectational errors. We also find that carry trading increases currency‐crash risk in that order flow generates negative skewness in FX returns.     

Cream-Skimming or Profit-Sharing? The Curious Role of Purchased Order Flow

Purchased order flow refers to the practice of dealers or trading locales paying brokers for retail order flow. It is alleged that such agreements are used to “cream skim” uninformed liquidity trades, leaving the information-based trades to established markets. We develop a test of this hypothesis, using a model of the stochastic process of trades. We then estimate the model for a sample of stocks known to be used in order purchase agreements that trade on the New York Stock Exchange (NYSE) and the Cincinnati Stock Exchange. Our main empirical result is that there is a significant difference in the information content of orders executed in New York and Cincinnati, and that this difference is consistant with cream-skimming.     

Does Order Flow Commonality Extend Across Trade Sizes and Securities?

We examine commonality in order imbalances across different types of securities and find that the extent of commonality is greater than previously documented. Order imbalances in portfolios of small stocks, large stocks, and closed-end funds have explanatory power for other portfolio returns even in the presence of own order flow. Our analysis of order flow composition reveals commonality in small and medium trades, but not in large trades, across portfolios. The activity from small-size trades is systemic, but not generally associated with returns on other securities. Order imbalances from larger size trades provide more information relevant to stock prices.     

Explaining Intraday Pattern of Trading Volume from the Order Flow Data

Based on a comprehensive order flow data from the Taiwan stock market, this study examines directly how the intraday pattern of trading volume is related to the trading behavior of both informed and uninformed traders. The results indicate that both informed and uninformed investors have a strong desire to place orders at the market open and the close. Most of the orders at the market open are conservative and hence are waiting orders for price priority. The findings show that intraday trading volume as well as the real orders from both types of investors are J-shaped. In addition, both information and liquidity trading can explain the intraday pattern of trading volume. However, the impact of liquidity trading on volume is slightly higher than that of information trading.