Market structure, informational efficiency and liquidity: An experimental comparison of auction and dealer markets

We report the results of 18 market experiments that were conducted in order to compare the call market, the continuous auction and the dealer market. Transaction prices in the call and continuous auction markets are much more efficient than prices in the dealer markets. The call market shows a tendency towards underreaction to new information. Execution costs are lowest in the call market and highest in the dealer market. The trading volume and Roll's (Journal of Finance (1984) 1127–1139) serial covariance estimator are inappropriate measures of execution costs in the present context. The relation between private signals, trading decisions and trading profits is analyzed.     

Adverse selection costs for NASDAQ and NYSE after decimalization

NYSE and NASDAQ completed their decimalization on January 29, 2001 and on April 9, 2001 respectively. In this paper, we compare adverse selection component of the bid–ask spread for NASDAQ and NYSE stocks after decimalization using the data from May 2001 and July 2001. We find that the adverse selection component of the bid–ask spread is significantly lower on NASDAQ than on NYSE, and these differences cannot be attributed to the differences in the characteristics of the stocks traded in the two markets. In addition, we find that the adverse selection costs increase with trade size on NYSE, however there is no monotonic pattern observed for NASDAQ stocks. Lastly, we report that although the order flows arrived in the two markets are significantly different, they can at best explain a small portion of the observed differences in adverse selection costs.     

Pricing behavior in an off-hours computerized market

Automated markets are becoming increasingly widespread, and their efficiency properties are of corresponding concern to regulators and exchange policy makers. Many systems are implemented in settings characterized by a distinct lack of liquidity, however, often by design. We evaluate the performance of such a market, the GLOBEX overnight trading system, in absolute terms and relative to a liquid benchmark, the floor market of the Chicago Mercantile Exchange (CME). Our results with respect to bid–ask spreads and adverse selection suggest that the nature of the environment is an important determinant of market performance, but that an automated market can operate well in a relatively illiquid setting. Price clustering, indicative of a lack of pricing efficiency, is prevalent on the automated system, but price resolution improves as trading frequency increases.     

Sources of liquidity for NYSE-listed non-US stocks

We examine the components of displayed (quoted) liquidity and the amount of non-displayed liquidity on the NYSE for a sample of non-US stocks. Consistently with prior work, non-US stocks have less displayed liquidity than similar US stocks. Extending prior research, we find that this is true both in the limit order book and on the floor. As Domowitz et al. [Domowitz, I., Glen, J., Madhavan, A., 1998. International cross-listing and order flow migration: Evidence from and emerging market. Journal of Finance 53, 2001–2027] posit, non-US stocks from transparent/linked home markets have more displayed NYSE liquidity when the home market is open but non-US stocks from opaque/non-linked home markets have more NYSE displayed liquidity when the home market is closed. Non-US and US stocks have similar supplies of non-displayed liquidity, consistent with the idea that the conditional nature of non-displayed liquidity allows NYSE traders to mitigate adverse selection problems inherent in trading non-US stocks. Our results imply that non-US stocks have less total (displayed plus non-displayed) liquidity than US stocks.     

The impact of mandatory IFRS reporting on institutional trading costs: Evidence from Australia

This study examines the impact of mandatory International Financial Reporting Standards (IFRS) on the market quality of the Australian Securities Exchange (ASX) 200 constituent stocks. Using traditional metrics that are consistent with prior literature (i.e., bid‐ask spreads), the first stage analysis confirms that stock liquidity has improved. However, when the analysis is extended to consider the trading costs incurred by market participants (i.e., execution shortfall), results suggest liquidity has not changed significantly. The paper utilizes rich unique datasets that contain detailed trade information, and findings are robust after controlling for trade difficulty and market conditions. In the era of High Frequency Trading (HFT) and occurrences of ‘fleeting’ liquidity, this paper provides some evidence that while IFRS may have enhanced ‘visible’ bid‐ask spreads, tangible liquidity for market participants, particularly global institutional investors, has not improved significantly.     

Market microstructure: A review from down under

The early automation of the Australian and New Zealand financial markets provided researchers with access to high‐frequency data to undertake extensive empirical market microstructure research. We use this anniversary edition of Accounting and Finance to review some of this research and to discuss the development of the Australian and New Zealand markets since their automation. We identify issues currently facing the markets and highlight potential areas for future research. The paper also provides a review of market microstructure theory on inventory control models and asymmetric information models.     

Optimal execution of open-market stock repurchase programs

This paper formalizes the following intuition about open-market share repurchases. Firms do open-market share repurchases to return free cash, which would otherwise be wasted. However, when the firm goes to buy its own shares with this cash, it has inside information and hence the actual execution is characterized by adverse selection. The market knows that the firm has inside information, and consequently the ask price is high to compensate for this adverse selection problem. This implies that, all else equal, the greater the adverse selection problem compared to the cash waste problem, the higher the ask price, and, therefore, the wider the bid–ask spread and the lower the share repurchase completion rate. We test this implication on a sample of U.S. firms and report evidence consistent with the model.     

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.     

Measures of implicit trading costs and buy–sell asymmetry

This paper shows that the widely documented buy–sell asymmetry in implicit institutional trading cost is mainly driven by mechanical characteristics of a specific class of measures: pre-trade measures. If a post-trade measure is used, the asymmetry is reversed in both rising and falling markets. Both pre-trade and post-trade measures are highly influenced by market movement, while during-trade measures are relatively neutral to market movement. I further show that a pre-trade measure can be decomposed into a market movement component and a during-trade measure, and empirically the market movement component is the dominant component. This paper demonstrates that simple mechanical characteristics of trading cost measures can have important implications for how empirical results are interpreted.     

An evolutionary multi‐objective optimization of trading rules in call markets

We evaluate an agent‐based model featuring near‐zero‐intelligence traders operating in a call market with a wide range of trading rules governing the determination of prices and which orders are executed, as well as a range of parameters regarding market intervention by market makers and the presence of informed traders. We optimize these trading rules using a multi‐objective population‐based incremental learning algorithm seeking to maximize the trading volume and minimize the bid–ask spread. Our results suggest that markets should choose a small tick size if concerns about the bid–ask spread are dominating and a large tick size if maximizing trading volume is the main aim. We also find that unless concerns about trading volume dominate, time priority is the optimal priority rule. Copyright © 2011 John Wiley & Sons, Ltd.     

Dynamics of financial markets and transaction costs: A graph-based study

In financial markets, trading patterns influence the behaviour of arbitrage, surveillance, risk management and pricing returns. The analysis of these patterns is important for defining policies in financial regulation as well as portfolios of international assets. Using financialization as a conceptual framework to understand the current trading patterns of financial markets, this work employs a market graph model for studying the stock indexes of geographically separated financial markets. By using an edge creation condition based on a transaction cost threshold, the resulting market graph features a strong connectivity, some traces of a power law in the degree distribution and an intensive presence of cliques. Furthermore, an inverse relation between transaction costs and maximal clique size is noticed. The market graph model also indicates that infrastructure, sustainability and commodity indexes from APEC, EU and NAFTA affect the behaviour of markets. As a result, the graph approach shows a consistent set of outcomes that mostly explain the financialization dynamics of markets.     

The rise and fall of technical trading rule success

The purpose of this paper is to examine the performance of an important set of momentum-based technical trading rules (TTRs) applied to all members of the Dow Jones Industrial Average (DJIA) stock index over the period 1928–2012. Using a set of econometric models that permit time-variation in risk-adjusted returns to TTR portfolios, the results reveal that profits evolve slowly over time, are confined to particular episodes primarily from the mid-1960s to mid-1980s, and rely on the ability of investors to short-sell stocks. These findings are demonstrated to be consistent with theoretical models that predict a relationship between TTR performance and market conditions.     

The relationship between stock returns and volatility in international stock markets

This study examines the relationship between expected stock returns and volatility in the 12 largest international stock markets during January 1980 to December 2001. Consistent with most previous studies, we find a positive but insignificant relationship during the sample period for the majority of the markets based on parametric EGARCH-M models. However, using a flexible semiparametric specification of conditional variance, we find evidence of a significant negative relationship between expected returns and volatility in 6 out of the 12 markets. The results lend some support to the recent claim [Bekaert, G., Wu, G., 2000. Asymmetric volatility and risk in equity markets. Review of Financial Studies 13, 1–42; Whitelaw, R., 2000. Stock market risk and return: an empirical equilibrium approach. Review of Financial Studies 13, 521–547] that stock market returns are negatively correlated with stock market volatility.     

The intraday multivariate structure of the Eurofutures markets

We investigate the multivariate intraday structure in interest rates, focusing on implied forward rates from Eurofutures contracts. Since futures markets are the most liquid for interest rate instruments and they yield high-quality intraday data, it is somehow surprising that their intraday behavior has not been thoroughly studied in the literature.We find interesting similarities with the foreign exchange market: scaling law, intraday patterns, all of which point to the heterogeneity of market participants. Other properties like asymmetric causal information flow between fine and coarse volatilities for the same time series are present in our data. There are also lead–lag correlations across the term structure of implied forward rates, but they tend to disappear as markets mature.A principal component analysis of the short end of the yield curve allows us to determine the most important components and to reduce the number of time series needed to describe the term structure. We find the decomposition rather stable over time. The first component, which describes the curve level, shows an asymmetry in the information flow between volatilities of different time resolution, i.e., the coarse-grained volatility predicts the fine-grained volatility better than the other way around, as observed in the foreign exchange market. The remaining components do not show such an effect, having instead significant negative autocorrelations for the time series themselves. A heterogeneous autoregressive conditional heteroskedasticity (HARCH) model is estimated for the first component and the impact of different market agents is discussed.     

The interrelatedness of global equity markets, money markets, and foreign exchange markets

This article investigates different aspects of global financial markets, specifically relationships among equity markets, money markets, and foreign exchange markets across countries. To represent the three major financial markets of the world, Japan is the proxy for Asia, Germany is the proxy for Europe, and the United States is the proxy for North America. Strong evidence exists that international money markets and international equity markets are becoming increasingly integrated over time. This article incorporates foreign exchange values as partial determinants of equity returns and money market returns and investigates the interactions among these three asset markets from a global perspective.     

The impact of competition and information on intraday trading

In a dynamic model of financial market trading multiple heterogeneously informed traders choose when to place orders. Better informed traders trade immediately, worse informed delay – even though they expect the market to move against them. This behavior generates intraday patterns with decreasing spreads, decreasing probability of informed trading (PIN), and increasing volume. We predict that policies that foster market entry improve the welfare of uninformed traders and lead to increased market participation by incumbent traders. Technological advances that lead to better signal processing also encourage market participation and increase volume but at the expense of uninformed traders’ welfare.     

The trading behavior of institutions and individuals in Chinese equity markets

This paper employs a unique data set to analyze the trading behavior of 4.74 million individual and institutional investors across Mainland China. Results show that groups of individual investors with varying trade values (as proxies for wealth levels) engage in different trading strategies. Chinese institutions are momentum investors, while less wealthy Chinese individual investors at large are contrarian investors. The results also indicate that a small group of wealthiest Chinese individuals tend to behave like institutions when they buy stocks, and behave like less wealthy individuals when they sell. Furthermore, only the trading activities of institutions and of wealthiest individuals can affect future stock volatility, but those of Chinese individual investors at large have no predictive power for future stock returns.     

Modeling and monitoring risk acceptability in markets: The case of the credit default swap market

Minimal discounted distorted expectations across a range of stress levels are employed to model risk acceptability in markets. Interactions between discounting and stress levels used in measure changes are accommodated by lowering discount rates for the higher stress levels. Acceptability parameters represent a maximal and minimal discount rate, a maximal stress level and the speed of rate reduction in response to stress. An explicit model relating credit default swap (CDS) prices to default probabilities is formulated with a view to making the default risk market acceptable. Data on CDS prices and default probabilities for the six major US banks obtained from the Risk Management Institute of the National University of Singapore is employed to estimate parameters defining acceptability and the movements in market implied recovery rates. We observe that the financial crisis saw an increase in the maximal discount rate and its spread over the minimal rate along with an increase in the maximal stress level being demanded for acceptability and a stable pattern for the speed of rate adjustment through the period. The maximal rate, rate spread and stress levels have come down but with periods in the interim where they have peaked as they did in the crisis. Recovery rates have oscillated and they did fall substantially but have recovered towards 40 percent near the end of the period.     

Market structure and competitive conditions in the Arab GCC banking system

This paper investigates the market structure of Arab GCC banking industry during the years of 1993–2002 using the most frequently applied measures of concentration k-bank concentration ratio (CRk) and Herfindahl–Hirschman Index (HHI) and evaluates the monopoly power of banks over the ten years period using the ‘H-statistic’ by Panzar and Rosse. The results show that Kuwait, Saudi Arabia and UAE have moderately concentrated markets and are moving to less concentrated positions. The measures of concentration also show that Qatar, Bahrain and Oman are highly concentrated markets. The Panzar–Rosse H-statistics suggest that banks in Kuwait, Saudi Arabia and the UAE operate under perfect competition; banks in Bahrain and Qatar operate under conditions of monopolistic competition; and we are unable to reject monopolistic competition for the banking market in Oman.     

The fall of high-frequency trading: A survey of competition and profits

We investigate high-frequency trading (HFT) strategies, inventorying the strategies already studied in the literature and introducing innovative strategies detected by private institutional research. To this end, we expand the existing classification, and we offer names for new categories. In a complementary but original manner, we introduce counter reactions from professional traders in response to HFT predatory strategies. These human answers reverse the usual framework of competition between high-frequency traders (HFTs) and low frequency traders (LFTs) and also widen this cadre to HFTs algos (predators) versus execution algos.This survey notes that a continuous increase in competition, between high-speed trading algorithms themselves through predatory strategies and from professional human traders adapting and building adequate responses has made the business more difficult and has led to shrinking profits for HFT. In the end, we believe that excessive competition and a change in the current regulation (favorable to HFT) could kill the goose that laid the golden egg.