DO DEALERS INFER INFORMATION FROM ORDER FLOW?

I examine strategic behavior among dealers in the NASDAQ market and document that there is a lead quote‐setting dealer in each security and that the quotes posted by this leader are informative. Other dealers free‐ride this information by following the lead quote‐setting dealer. The lead dealer can be identified by two information signals: (1) percentage of time spent on the inside market (i.e., posting inside quotes), and (2) trade volume transacted. Dealers that free‐ride the leader's quotes quickly update their posted quotes in the same direction as the leader's quote change. My findings suggest that directing trade to the lead dealer may be more advantageous than randomly routing trade.     

Semi‐transparency,dealership market,and foreign exchange market quality

This paper examines the effects of a semi-transparency event, the introduction of the electronic trading system (EBS), on the market quality of a typical dealership market – the FX market. We find that increasing transparency leads to smaller quote disagreement among dealers and higher trading volume, but the beneficial effects are bigger for uninformed dealers than informed dealers. We also find that information efficiency improves overall in the semi-transparent system; however, informed dealers are found to quote less aggressively in the more transparent market. We conclude that semi-transparency raises market quality in general, but that it is the uninformed dealers who benefit more from this increased quality.     

Quote revision and information flow among foreign exchange dealers

In a multi-dealer market without transaction disclosure, quote revision partially reveals the posting dealer's private information/belief and may have an impact on other dealers’ pricing decision. Using continuous quotes from three major dealers in the interbank foreign exchange market, I find significant information externality from one dealer's quotes to others. The information content of quote revision is positively related to the overall order flow to the market, as opposed to order flow to the posting dealer. At 15-min interval or above, public information becomes the dominant component that drives quote revision. Furthermore, public information appears to induce positive serial correlation and private information causes negative serial correlation in short-term quote revision.     

Risk Aversion, Transparency, and Market Performance

Using a model of market making with inventories based on Biais (1993), we find that investors obtain more favorable execution prices, and they hence invest more, when markets are fragmented. In our model, risk-averse dealers use less aggressive price strategies in more transparent markets (centralized) because quote dissemination alleviates uncertainty about the prices quoted by other dealers and, hence, reduces the need to compete aggressively for order flow. Further, we show that the move toward greater transparency (centralization) may have detrimental effects on liquidity and welfare.     

Can quote competition reduce preferenced trading? A reexamination of the SEC’s 1997 order handling rules

In 1997, the SEC implemented the new order handling rules (OHRs) on the NASDAQ. We observe that some uncompetitive positions gained market share without improving quote competitiveness after the implementation of the OHRs. Also observed is a significant decline in the sensitivity of trading volume to quote competitiveness, indicating lower incentive for NASDAQ dealers to engage in quote competition in the post‐OHR regime. We find that positions that gained trading volume without improving quote competitiveness were less competitive and were more closely associated with stocks showing low information asymmetry, which suggests that preferenced trading might be responsible for the decline in the trading volume sensitivity. Examining entries and exits around the periods of adopting OHRs, we observe net entry of uncompetitive positions and net exit of competitive positions, which indicates that preferenced trading crowded out quote competition subsequent to the OHRs. Our findings suggest that forcing intense quote competition alone produced an unwanted effect that preferencing emerged as a more attractive alternative to quote competition.     

PRICE AND QUANTITY QUOTES ON NASDAQ: A STUDY OF DEALER QUOTATION BEHAVIOR

We show that the majority of quotes posted by NASDAQ dealers are noncompetitive and only 19.5% (18.4%) of bid (ask) quotes are at the inside. The percentage of dealer quotes that are at the inside is higher for stocks with wider spreads, fewer market makers, and more frequent trading, and lower for stocks with larger trade sizes and higher return volatility. These results support our conjecture that dealers have greater incentives to be at the inside for stocks with larger market‐making revenues and smaller costs. Dealers post large depths when their quotes are at the inside and frequently quote the minimum required depth when they are not at the inside. The latter quotation behavior leads to the negative intertemporal correlation between dealer spread and depth.     

A study on foreign exchange dealers' bid–ask spread quote behavior

Based on a questionnaire surveying dealers in the Taipei inter-bank foreign exchange market that was conducted in March 2001, I attempted to answer the question of who initiated the wider currency spread. It was found that the risk-averse dealers of small banks quoted wider spreads in order to conceal their inferior positions regarding information and inventory or to avoid market volatility risk. Some of the dealers of large multinational banks in major financial centers who normally quote conventional spreads were found to quote wider spreads in response to the request for quotations by small Taiwanese bank dealers who widened their spread quotes.     

Price discovery in currency markets

This paper examines the price discovery process in currency markets, basing its analysis on the pivotal distinction between the customer (end-user) market and the interdealer market. It first provides evidence that this price discovery process cannot be based on adverse selection between dealers and their customers, as postulated in standard models, because the spreads dealers quote to their customers are not positively related to a trade’s likely information content. The paper then highlights three factors familiar in the literature – fixed operating costs, market power, and strategic dealing – that may explain the cross-sectional variation in customers’ spreads. The paper finishes by proposing a price discovery process relevant to liquid two-tier markets and providing preliminary evidence that this process applies to currencies.     

Market Making with Costly Monitoring: An Analysis of the SOES Controversy

This article presents a model of information monitoring andmarket making in a dealership market. We model how intensivelydealers monitor public information to avoid being picked offby professional day traders when monitoring is costly. Pricecompetition among dealers is hampered by their incentives toshare monitoring costs. The risk of being picked off by theday traders makes dealers more competitive. The interactionbetween these effects determines whether a firm quote rule improvestrading costs and price discovery. Our empirical results supportthe prediction that professional day traders prefer stocks withsmall spreads, but offer less support for the prediction thattheir trading leads to wider spreads.     

ANALYST REPUTATION,DEALER AFFILIATION,AND MARKET MAKING

We investigate the effects of analysts' affiliation and reputation on dealers' market making activities. We find that for a given stock, dealers who have affiliated analysts covering the stock quote and trade more aggressively than those who do not have any affiliated analysts. More important, the reputation of affiliated analysts plays an additional role in the affiliated dealer's quote and trade behavior. Dealers with affiliated star analysts post more aggressive quotes and have larger market shares than dealers with affiliated nonstar analysts. Although dealers who post more aggressive quotes also induce affiliated star analysts to cover the stocks, the positive effect of analyst reputation on the affiliated dealers' quote aggressiveness remains significant and robust after controlling for potential endogenous and simultaneous problems.     

Dealer attention,the speed of quote adjustment to information,and net dealer revenue

Using trade and quote data from the NYSE, we examine the relation between dealer attention, dealer revenue, and the probability of informed trade. We find that dealer revenue net of losses to better-informed traders in NYSE stocks is positively related to the speed at which quotes adjust to full information levels. The speed of quote adjustment is faster for stocks with greater dealer attention, as measured by a stock’s relative prominence at its post and panel location on the NYSE floor. The level of dealer attention in turn is positively related to a stock’s probability of information-based trading. The results are consistent with a theoretical model we derive in which dealers trade multiple securities and must optimally allocate their limited attention to monitoring order flow to minimize losses to better-informed traders.     

Portfolio risk,adjustment costs,and security dealers' bid/ask spreads

This article notes that dealers' bid/ask spreads should vary directly with their costs of adjusting to inventory imbalances. Thus, well-diversified dealers are expected to quote lower bid/ask spreads on stocks with substantial total risk caused by undiversifiable risk. Furthermore, the effect of systematic risk on bid/ask spreads should be negligible if dealers are compensated for systematic risk by market returns. This article shows that, empirically, bid/ask spreads of OTC stocks are insensitive to the systematic risk of individual stocks—even when only stocks with stable betas are considered. Furthermore, bid/ask spreads are not sensitive to changes in market variance, as would be expected if systematic risk affected spreads. While unsystematic risk affects bid/ask spreads, its effect is pronounced for stocks traded by small, undiversified dealers. If stocks are only traded by large dealers with low diversification costs, unsystematic risk does not affect bid/ask spreads.     

Institutional investor information network,analyst forecasting and stock price crash risk

In this paper, we construct the information network of fund investors based on the theory of social relationship networks and examine its impact of fund information sharing with analysts on stock price crash risk. Our results show that private information sharing among institutional investors reduces crash risk. Further results show that fund information sharing can alleviate analyst optimism bias and improve analyst forecast accuracy, which further reduces stock price crash risk. Moreover, these identified effects are more pronounced in a bull market than a bear market. Our study contributes to the research on private information transmission in fund information networks, and provides a new perspective for recognizing the relationships among institutional investor behavior, analyst forecasting, and stock price crash risk.     

Intermediaries and product quality in used car markets

We present empirical evidence supporting that used cars sold by dealers have higher quality: (i) dealer transaction prices are higher than unmediated market prices, and this dealer premium increases in the age of the car as a ratio and is hump-shaped in dollar value, and (ii) used cars purchased from dealers are less likely to be resold. In a model, we show that these empirical facts can be rationalized either when dealers alleviate information asymmetry, or when dealers facilitate assortative matching. The model predictions allow us to distinguish these two theories in the data, and we find evidence for both.     

Information interaction among institutional investors and stock price crash risk based on multiplex networks

Using a large sample of A-share listed companies on the Chinese stock market, we investigate the impact of information interaction among institutional investors (IIAII) on stock price crash risk. IIAII is measured using a multiplex network constructed from data on the multiple social relations of institutional investors. We find a positive and significant relationship between IIAII and crash risk. The results of the influencing mechanism analysis show that IIAII influences crash risk through the herd effect rather than the monitoring effect. Overall, our findings elucidate the important role of institutional investors in corporate governance and promote the application of multiplex network theory to the financial field.     

Dealer Networks

Dealers in the over‐the‐counter municipal bond market form trading networks with other dealers to mitigate search frictions. Regulatory data show that this network has a core‐periphery structure with 10 to 30 hubs and over 2,000 peripheral broker‐dealers in which bonds flow from periphery to core and partially back. Central dealers charge investors up to double the round‐trip markups compared to peripheral dealers. In turn, central dealers provide immediacy by matching buyers with sellers more directly and prearranging fewer trades, especially during stress times. Investors thus face a trade‐off between execution cost and speed, consistent with network models of decentralized trade.     

The Declining Role of NASDAQ Market Makers

We compare the liquidity providing behavior of NASDAQ market makers in 2010 to their behavior in 2004. We examine how frequently market makers are at the inside quote, what market and stock specific factors influence market makers’ behavior, and the relation between market maker participation and intraday bid‐ask spread patterns. We observe a decrease in the percent of the trading day dealers’ quote at the inside, a decline in the number of market makers, and a decrease in the influence market makers have on intraday spread patterns. The results suggest that the role of NASDAQ market makers declines over time.     

Informed trading in hybrid bond markets

I study the impact of pretrade transparency on trading activity in an environment where dealers, informed and uninformed alike, can choose between an electronic limit order book (LOB) and an over-the-counter (OTC) market. By investigating bond dealers' choice in the hybrid Norwegian government bond market, I explore whether they base their trading strategy on the perceived informativeness of their trades. The results imply that bond dealers act strategically to preserve the value of their information by choosing the immediacy of the LOB when trades contain information. This suggests that OTC trades are exposed to a leakage of information to other dealers.     

Thinking and Learning in the Tax Evasion Game

Equilibrium behaviour is one of the fundamental concepts of economics: that each player's strategy is a best response to their beliefs about other players' strategies (and that these beliefs are realised). It is therefore striking that one of the most utilised economic models of tax compliance (Allingham and Sandmo, 1972) lacks this property as random audit selection is not a best response for the tax administration. The game theory literature of tax compliance has solved the equilibrium under assumptions of perfect information, full rationality and representative agents (Reinganum and Wilde, 1986; Erard and Feinstein, 1994). The recent application of behavioural economics to tax compliance (Hashimzade et al., 2014) allows richer assumptions such as heterogeneity and asymmetric information to be included in agent‐based models. This paper investigates the tax administration's best‐response audit strategy with heterogeneous taxpayers, imperfect information and evolutionary survival of taxpayers. It finds that, under these conditions, the tax administration's best‐response audit strategy is an adaptive learning approach and not a well‐defined audit function. This fits with actual practice of ‘predictive analytics’ by OECD tax administrations. Behavioural game theory also predicts that when actors are information rich, adaptive learning will dominate abstract thinking.     

Foreign Under‐Investment in US Securities and the Role of Relational Capital

Over 70 academic papers attempt to explain why foreigners invest in US securities. All ignore the vital role of the US broker‐dealer. Macroeconomic factors like a trade balance or corporate governance may guide foreign investors toward certain markets. But US broker‐dealers provide information to foreign investors and execute the actual trades. We hypothesize that particular foreign investors under‐invest in US securities because of a lack of relational capital with US broker‐dealers. We find that broker‐dealer marketing intensity in foreign markets partly explains foreigners’ decisions to invest in US securities. We also estimate “pent‐up” demand for US securities in developing countries – like China, Argentina, Turkey and Russia –equals roughly half‐a‐trillion dollars. Such pent‐up demand – represented as a convergence gap with investment‐to‐GDP ratios in highly developed capital markets – helps predict which markets these broker‐dealers are likely to invest marketing effort in the future. As such, broker‐dealers interested in assisting foreign investors find the right securities for their portfolios should not focus on big, rich economies. They should focus on economies with the largest convergence gaps. We also find that broker‐dealers must take in account the effect their marketing effort has on the typical variables (like relative returns, risks, asymmetric shocks and communication with the US) when they use these screening variables in deciding where to build their relational capital (and place their sales effort) in any year.