Competition in the stock market with asymmetric information

We build a game theoretical model to examine how the level of information advantage of insiders and the competition between insiders and sophisticated investors affect stock price movements and traders’ trading strategies and profits. We show that the competition between insiders and sophisticated investors can reduce the losses of less sophisticated investors, and thus alleviates the disadvantaged position of the less sophisticated investors. Further, traders’ profits are affected by the accuracy of insiders’ private information, and the number of days that insiders have obtained the information in advance. These findings show the importance of information transparency and the role of sophisticated investors in limiting insiders’ trading advantages and mitigating the expropriation of investors by insiders.     

The Effects of Subject Pool and Design Experience on Rationality in Experimental Asset Markets

Empirical evidence suggests that prices do not always reflect fundamental values and individual behavior is often inconsistent with rational expectations theory. We report the results of fourteen experimental asset markets designed to examine whether the interactive effect of subject pool and design experience (i.e., previous experience in a market under identical conditions) tempers price bubbles and improves forecasting ability. Our main findings are: 1) price run-ups are modest and dissipate quickly when traders are knowledgeable about financial markets and have participated in a previous market under identical conditions; 2) price bubbles moderate quickly when only a subset of traders are knowledgeable and experienced; 3) the heterogeneity of expectations about price changes is smaller in markets with knowledgeable and experienced traders, even if such traders only represent a subset of the market; and 4) individual forecasts of prices are not consistent with the predictions of the rational expectations model in any market, although absolute forecast errors are smaller for subjects who are knowledgeable of financial markets and for those subjects who have participated in a previous market. In sum, our findings suggest that markets populated by at least a subset of knowledgeable and experienced traders behave rationally, even though average individual behavior can be characterized as irrational.     

Efficiency of continuous double auctions under individual evolutionary learning with full or limited information

In this paper we explore how specific aspects of market transparency and agents’ behavior affect the efficiency of the market outcome. In particular, we are interested whether learning behavior with and without information about actions of other participants improves market efficiency. We consider a simple market for a homogeneous good populated by buyers and sellers. The valuations of the buyers and the costs of the sellers are given exogenously. Agents are involved in consecutive trading sessions, which are organized as a continuous double auction with order book. Using Individual Evolutionary Learning agents submit price bids and offers, trying to learn the most profitable strategy by looking at their realized and counterfactual or “foregone” payoffs. We find that learning outcomes heavily depend on information treatments. Under full information about actions of others, agents’ orders tend to be similar, while under limited information agents tend to submit their valuations/costs. This behavioral outcome results in higher price volatility for the latter treatment. We also find that learning improves allocative efficiency when compared to outcomes with Zero-Intelligent traders.     

Market manipulation with sentiment traders

This article offers a new perspective for traders’ sentiment by bridging the relationship between feedback effect and market manipulation. Allowing access to information regarding manipulated orders confuses sentiment traders, leading to an overestimation of the true asset value which actually remains the same. We find that sentiment factor has a nonmonotonic impact on the responsiveness to order information and price informativeness. Furthermore, it is shown that informed traders behave like a contrarian, and can use order information to reassess the price, which results in the multiplicity of equilibria.     

Informed manipulation

In asymmetric information models of financial markets, prices imperfectly reveal the private information held by traders. Informed insiders thus have an incentive not only to trade less aggressively but also to manipulate the market by trading in the wrong direction and undertaking short-term losses, thereby increasing the noise in the trading process. In this paper we show that when the market faces uncertainty about the existence of the insider in the market and when there is a large number of trading periods before all private information is revealed, long-lived informed traders will manipulate in every equilibrium.     

异质信念、投机均衡与农产品期货定价*

农产品期货市场套利并不充分,交易者也不是完全理性的。本文假设农产品期货市场有限套利、交易者异质信念并遵循“经验法则”预期,构建了农产品期货投机均衡定价模型,并认为集中竞价规则下产生的农产品期货价格是由交易者的预期决定的;前期期货价格水平、现货价格和前期期货价格的变动趋势、不同类型交易者的比例结构及其预期模式共同影响农产品期货价格的形成与波动;基本分析法交易者占主导地位的农产品期货市场具有更高的套期保值与价格发现效率。针对中国七种主要农产品期货的实证结果显示,农产品期货投机均衡定价模型对解释中国农产品期货价格的形成与波动是有效的。这意味着在期货行情系统中实时披露现货价格信息,培育和引导交易者运用基本分析法预测期货价格走势,有助于提升农产品期货市场的效率。     

Conservative traders,natural selection and market efficiency

This paper examines the impact of conservative traders on market efficiency in an evolutionary model of a commodity futures market. This paper shows that the long-run market outcome is informationally efficient, as long as in every period there is a positive probability that entering traders are more conservative than their predecessors. Conservative traders are those who correctly predict the spot price with a positive probability, and more importantly, who in their mistakes err on the side of caution, and rarely overpredict the spot price as buyers, and underpredict the spot price as sellers. This result does not require entry of traders with better information than their predecessors.     

Strategic Information Acquisition in Capital Markets*

A simple model of an asset market is presented, where agents are asymmetrically informed and hence information is transmitted through the price system. Prior to the trading period, a group of traders is given the opportunity to decide in a collusive arrangement whether they want to undertake a (costless) analysis which yields information about the future dividends of a risky asset. It will be shown that the fully rational and risk-averse insiders can do better without the information, if the dividend volatility of the risky asset is sufficiently low.
JEL Classification Numbers: D82, G14.     

Is the corn futures market noisier? The impact of high frequency quoting

ABSTRACT

The paper pioneers research on high frequency (HF) quoting noise in electronically traded agricultural futures markets. HF quoting – quickly cancelling posted limit orders and replacing them with new ones – emerges as a strategy for liquidity-providing traders. HF quoting can generate noise in price quotes which adds uncertainty to order execution and impairs the informational value of bid and ask prices. It can also lead to the perception that markets cannot be trusted for commercial transactions. Using intraday Best Bid Offer data for 2008–2013 and wavelet-based measures of volatility, we investigate the excess variance and co-movement discrepancies in the bid and ask prices. We find excess HF quoting variance exists. It is the highest at 250-ms scale – 90% higher than the variance implied by a random walk – but declines quickly to 7% at the 32 s scale. But its economic magnitude is negligibly small. Bid and ask price co-movements show a low degree of discrepancy with average correlations at 0.67 at 250 ms and reaching 0.95 at 8 s. All measures indicate that HF quoting noise has declined through the period. Overall, HF quoting has not caused excess variance during the transition to electronic trading in the liquid corn futures market.     

Information aggregation in experimental asset markets in the presence of a manipulator

We study with the help of a laboratory experiment the conditions under which an uninformed manipulator—a robot trader that unconditionally buys several shares of a common value asset in the beginning of a trading period and unwinds this position later on—is able to induce higher asset prices. We find that the average price is significantly higher in the presence of the manipulator if and only if the asset takes the lowest possible value and insiders receive perfect information about the true value of the asset. It is also evidenced that the robot trader makes trading gains. Finally, both uninformed and partially informed traders may suffer from the presence of the robot.     

Limit orders,asymmetric information,and the formation of asset prices with a computerized specialist

We analyze the existence of equilibrium in an asset market under asymmetric information. Price formation is modeled as a bilateral sealed bid auction where uninformed and informed traders submit limit orders to a computerized specialist. The computerized specialist is programmed to sell to the highest bidder and buy from the seller asking the lowest price. We show that this mechanism — which is designed to model the Globex and RAES trading institutions used in Chicago, London, New York, Paris, and Germany — yields an equilibrium in which the bid-ask spread is endogenously random and the passive specialist earns nonnegative profits.     

Rock around the clock: An agent-based model of low- and high-frequency trading

We build an agent-based model to study how the interplay between low- and high-frequency trading affects asset price dynamics. Our main goal is to investigate whether high-frequency trading exacerbates market volatility and generates flash crashes. In the model, low-frequency agents adopt trading rules based on chronological time and can switch between fundamentalist and chartist strategies. By contrast, high-frequency traders activation is event-driven and depends on price fluctuations. High-frequency traders use directional strategies to exploit market information produced by low-frequency traders. Monte-Carlo simulations reveal that the model replicates the main stylized facts of financial markets. Furthermore, we find that the presence of high-frequency traders increases market volatility and plays a fundamental role in the generation of flash crashes. The emergence of flash crashes is explained by two salient characteristics of high-frequency traders, i.e., their ability to i. generate high bid-ask spreads and ii. synchronize on the sell side of the limit order book. Finally, we find that higher rates of order cancellation by high-frequency traders increase the incidence of flash crashes but reduce their duration.     

Price Limits, Information Acquisition, and Bid–ask Spreads: Theory and Evidence

A number of futures markets use price limits which, in effect, preclude trade from occurring at prices outside certain exogenous bounds. Noting that such markets are characterized by heterogeneously informed traders, whereas previous work on price limits assumes symmetrically informed traders, we examine the effects of price limits in a setting where market participants are asymmetrically informed. We find that imposing price limits generally lowers the quality of information acquired in equilibrium, but lowers bid–ask spreads as well. Thus, depending on the relative weights placed by society on liquidity versus price efficiency, there may exist a set of price limits that are most efficient in achieving a trade-off between liquidity and informational efficiency. We perform empirical tests of some implications of the model using cross-sectional data on price limits. We find that price limits are strongly negatively related to both price volatility and trading volume. Though other explanations for our empirical findings cannot be ruled out, these results are not inconsistent with the model's implication that price limits should be tighter for contracts which offer greater profit potential for informed traders.     

Market maker competition and price efficiency: Evidence from China

We test the relationship between market maker competition and stock price efficiency. Using the number of market makers as a proxy for competition, the results show a strong positive correlation between competition and stock price efficiency. Moreover, price efficiency is higher when competing market makers have higher research ability. We suggest that market maker competition increases price efficiency through two channels: 1) Competition decreases transaction costs, and 2) Uninformed market makers learn from orders submitted by informed market makers through competition. The latter happens only in the group of market makers with higher experiences. The results imply that the price efficiency can be improved by enhancing the competition of market makers with high research ability and experiences.     

融券制度与内部人寻租——来自准自然实验的经验证据

内部人寻租一直以来是理论与实务界关心的重点,如何有效抑制内部人寻租行为是资本市场的重大课题。本文以内部人交易度量内部人寻租,分析了融券制度对内部人寻租的影响。研究发现:(1)融券制度对内部人寻租有显著抑制作用,并且融券规模越大,内部人寻租越少。(2)相比于国有企业,非国有企业当中融券制度对内部人寻租的抑制作用更加明显。本文还将内部人交易分方向进行回归,结果显示融券制度对内部人寻租的抑制作用主要体现在卖出方向上。本文进一步分析了融券制度影响内部人寻租的路径,发现“竞争效应”和“信息效应”是融券制度影响内部人寻租的两条重要路径。本文考虑了竞争性解释——分析师关注的作用,发现分析师关注并不能影响本文结论的正确性;本文还利用反面事实推断、倾向得分匹配、反向因果检验等方法,确保实证结论的稳健性。本文的研究结果,丰富了内部人寻租的特征及影响因素研究,有利于市场监管部门加强对内部人寻租行为的控制;扩充了有关融券制度的文献,为卖空制度的推行及完善提供理论依据。     

Experimental asset markets with endogenous choice of costly asymmetric information

Asymmetric distribution of information, while omnipresent in real markets, is rarely considered in experimental financial markets. We present results from experiments where subjects endogenously choose between five information levels (four of them costly). We find that (i) uninformed traders earn the highest net returns, while average informed traders always perform worst even when information costs are not considered; (ii) over time traders learn to pick the most advantageous information levels (full information or no information); and (iii) market efficiency decreases with higher information costs. These results are mostly in line with the theoretical predictions of Grossman and Stiglitz (Am. Econ. Rev. 70:393–408, 1980) and provide additional insights that studies with only two information levels cannot deliver.     

Convergence of outcomes and evolution of strategic behavior in double auctions

We study the emergence of strategic behavior in double auctions with an equal number of buyers and sellers, under the distinct assumptions that orders are cleared simultaneously or asynchronously. The evolution of strategic behavior is modeled as a learning process driven by a genetic algorithm. We find that, as the size of the market grows, allocative inefficiency tends to zero and performance converges to the competitive outcome, regardless of the order-clearing rule. The main result concerns the evolution of strategic behavior as the size of the market gets larger. Under simultaneous order-clearing, only marginal traders learn to be price takers and make offers equal to their valuations/costs. Under asynchronous order-clearing, all intramarginal traders learn to be price makers and make offers equal to the competitive equilibrium price. The nature of the order-clearing rule affects in a fundamental way what kind of strategic behavior we should expect to emerge.     

Strategic noise traders and liquidity pressure with a physically deliverable futures contract

Do physically deliverable futures contracts induce liquidity pressure in the underlying spot market? The answer is believed to be no since the asset is delivered sometimes after the expiration of the contract so that the futures trader's payoff does not clearly depend on the price of the underlying stock at expiration. We construct a rational expectations equilibrium model in which a strategic uninformed trader induces liquidity pressure in the underlying spot market at the expiration of a physically deliverable futures contract. Liquidity pressure is the result of a pure informational advantage: if it is known that futures traders hedge their position in the spot market then a strategic trader with no information about the fundamental value of the underlying has an incentive to create noise in the futures market in order to gain information on the composition of the spot order flow at future auctions. We show that informed traders benefit from this form of strategic noise and that the efficiency of the prices remains unaffected.     

Do insiders have inside tracks: An examination of Wall Street Journal's Inside Track columns?

This study investigates how the stock market reacts to the publications of the Wall Street Journal's “Inside Track” columns in two distinct time periods, 1988 to 1993 and 2002 to 2004. It first examines the stock return behavior during the trading period, the filing period, and the publication day for firms appeared in the Inside Track columns in the period of 1988 to 1993 and then provides a validity test with a sample from 2002 to 2004. The evidence indicates that the market tends to under-react to the insider trading information and insiders tend to be information-motivated traders. The significant filing period returns along with significant publication period returns are consistent with the gradual price adjustment argument. The study also finds that market reactions to the publications are significantly related to insider trading when the trades involve the board chairman.     

Evolution of trading strategies in a market with heterogeneously informed agents

We present an agent-based simulation of an asset market with heterogeneously informed agents. Genetic programming is applied to optimize the agents’ trading strategies. After optimization, insiders are the only agents able to generate small systematic above-average returns. For all other agents, genetic programming finds a rich variety of trading strategies that are predominantly based on exclusive subsets of their information. This limits their price impact and prevents them from making systematic losses. The resulting low noise renders market prices as largely informationally efficient.