Rational panics and stock market crashes

This paper offers an explanation for stock market crashes which focuses on the role of rational but uninformed traders. We show that uninformed traders can precipitate a price crash because as prices decline, they surmise that informed traders received negative information, which leads them to reduce their demand for assets and drive the price of stocks even lower. The model yields several implications, such as that crashes can occur even when the fundamentals are strong, and that the magnitude of the crash depends on the fraction of uninformed investors and the amount of unsophisticated passive investing present in the market.     

Herding effects in order driven markets: The rise and fall of gurus

We introduce an order driver market model with heterogeneous traders that imitate each other on a dynamic network structure. The communication structure evolves endogenously via a fitness mechanism based on agents performance. We assess under which assumptions imitation, among noise traders, can give rise to the emergence of gurus and their rise and fall in popularity over time. We study the wealth distribution of gurus, followers and non followers and show that traders have an incentive to imitate and a desire to be imitated since herding turns out to be profitable. The model is then used to study the effect that different competitive strategies (i.e. chartist & fundamentalist) have on agents performance. Our findings show that positive intelligence agents cannot invade a market populated by noise traders when herding is high.     

Intraday trade in dealership markets

We develop and test a structural asymmetric information transaction model to characterize the price impact of information when markets are thin. Since orders are accepted individually, the model allows for transaction costs and brokerage fees. Equilibrium demands mixed entry strategies on the part of potentially informed traders. Estimation of the structural parameters is performed using a maximum likelihood procedure on NYSE data. The structural model is rejected primarily because the nonlinear restrictions do not allow for sufficient correlation between price movements and pricing errors. This leads to unreasonably low estimates of the probability of informed trade relative to an unrestricted alternative. The price impact of information is found to be positive and significant, but economically small. This is because although the amount of private information is substantial, the quality of the information signals is poor, particularly in the middle of the trading day. Informed agents do not trade small quantities, which suggests that their ability to divide orders is limited by transaction costs.     

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.     

Informed trading and the ‘leakage’ of information

This paper examines the effect of ‘leakage’ of information, private information becoming available to uninformed traders at a later date, on information acquisition and revelation. Using a Shapley-Shubik market game framework it is shown that (a) if information acquisition by the informed traders is costless, this leads to faster revelation of information; (b) if information acquisition is costly, there may be no acquisition of information; (c) information leakage leads to a fall in value of information but does not affect the incentive for informed traders to sell the information.     

Revisiting the Lemons Market

This article extends the standard competitive adverse selection model by allowing for qualitatively different information structures of agents on the informed side of the market. Using the stylized framework of the market for used cars, we examine the welfare properties of equilibria under the assumption that a fraction of the sellers remains uninformed about a parameter that is relevant for their own transaction. Whether market performance increases or decreases in the number of uninformed sellers is shown to depend on (1) the potential gains from trade in the market and (2) the average quality of the sellers' information structure.     

Marketmaking in the Laboratory: Does Competition Matter?

This paper is the first experimental study of the effects of competition and adverse selection on the performance of market maker (MM-) markets. Information distribution may is either symmetric or heterogeneous. MM-markets are either monopolistic (the specialist markets), or competitive (the multi MM-market). Welfare comparisons are with respect to a continuous double auction (DA-) market. Informed subjects receive an imperfect signal of the true state of the world. We find three main results. First, competition among market makers significantly reduces the bid-ask spread, and increases transaction volume. Second, competition among market makers induces competitive undercutting, yielding net trading losses for market makers as a group in most periods. Third, from the perspective of uninformed traders, a competing MM-regime is optimal, since it minimizes their expected trading losses.     

When and Where Are Informed Traders? What Is Their Relationship with Analysts in the Price Discovery Process?

The authors' aim was to analyze the influence of analysts' recommendations on the activity of informed and uninformed traders and whether such influence produces changes in the price discovery process. The analysis was carried out in the Spanish market, considered to be an ideal market given its characteristics. The authors' results indicate that although investors as a whole react to new information from analysts and their activity increases, this reaction is not independent of the type of stock. Informed traders do not increase their activity with small stocks to the same extent as uninformed investors do. Furthermore, the influence of these movements on price discovery is not significant. The results suggest that the interpretation role of analysts is more important for less accessible firms in terms of assessing their growth opportunities. This role may enhance the herding behavior of uninformed agents trading in those small titles for which they would otherwise need to invest extra time and extra money for taking profitable decisions.     

Timing under individual evolutionary learning in a continuous double auction

The moment of order submission plays an important role for the trading outcome in a Continuous Double Auction; submitting an offer at the beginning of the trading period may yield a lower profit, as the trade is likely to be settled at the own offered price, whereas late offers result in a lower probability of trading. This timing problem makes the order submission strategy more difficult. We extend the behavioral model of Individual Evolutionary Learning to incorporate the timing problem and study the limiting distribution of submission moments and the resulting offer function that maps submission moments to offers. We find that traders submit different offers at different submission moments the distribution of which uni-modal with a peak moving from late to early as the market size increases. This behavior exacerbates efficiency loss from learning. If traders evaluate profitability of their strategies over longer history, orders are submitted later with the same effect of market size.     

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.     

Liquidity supply and adverse selection in a pure limit order book market

This paper analyzes adverse selection costs and liquidity supply in a pure open limit order book market. We relax assumptions of the Glosten/Såndas modeling framework regarding marginal zero profit order book equilibrium and the parametric market order size distribution. We show that using average zero profit conditions considerably increases the empirical performance while a nonparametric specification for market order size combined with marginal zero profit conditions does not. A cross sectional analysis corroborates the finding that adverse selection costs are more severe for smaller capitalized stocks. We also find additional support for one of the central hypothesis put forth by the theory of limit order book markets, which states that liquidity supply and adverse selection costs are inversely related. Furthermore, adverse selection cost estimates based on our structural model and those obtained using popular model-free methods are strongly correlated. This indicates the robustness of the theory-based approach.     

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.     

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.     

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.     

Insider trading with public and shared information

We study the impact of public information and shared information on traders' trading behavior in the context of Kyle's (1985) speculative market. We suppose that there are four types of traders in our model: one insider, M outsiders, liquidity traders, and market makers. We explicitly describe the unique linear Nash equilibrium and find that public information harms the insider but benefits the outsiders and noise traders. Also, the market is more efficient because of the existence of public information.     

成交风险、交易成本、逆向选择风险与投资者订单选择

本文利用多元对教条件自田归计数模型讨论了交易概率、交易成本以及选择成本等市场微观结构因素对中国证券市场投资者订单选择的影响.实证研究发现:(1)交易成本的增加会削弱投贵者递交指令的积极性,当成交风险较大时,投资者更偏好市价订单;(2)由于中国证券市场订单类型较为单一,逆向选择风险对投资者订单选择行为并无显著性的影响;(3)在同质信息的驱动下不同类型订单之间具有显著的持续和交叉相关性.     

Market for Information and Identity Disclosure in an Experimental Open Limit Order Book

This paper analyses the effects of pre‐trade transparency on market quality in an experimental open limit order book preceded by a market for information. The design of the trading game is akin to the system in use in an increasing number of financial markets. We find that the disclosure of traders' identities reduces the incentive to acquire information, liquidity and volatility. We also show that a positive relation exists between the proportion of traders buying information and liquidity. The results are consistent with a standard model of price formation where the number of informed traders is endogenous .     

Price efficiency and trading behavior in limit order markets with competing insiders

We study price efficiency and trading behavior in laboratory limit order markets with asymmetrically informed traders. Markets differ in the number of insiders present and in the subset of traders who receive information about the number of insiders present. We observe that price efficiency (i) is the higher the higher the number of insiders in the market but (ii) is unaffected by changes in the subset of traders who know about the number of insiders present. (iii) Independent of the number of insiders, price efficiency increases gradually over time. (iv) The insiders’ information is reflected in prices via limit (market) orders if the asset’s value is inside (outside) the bid-ask spread. (v) In situations where limit and market orders yield positive profits, insiders clearly prefer market orders, indicating a strong desire for immediate transactions.     

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.     

Price Competition and Consumer Externalities in a Vertically Differentiated Duopoly with Information Disparities

In this paper, we extend the model of vertical product differentiation to consider information disparities about quality differences and their effects on price competition. If uninformed consumers overestimate vertical differentiation, asymmetric information is a source of market power and informed consumers exert positive externalities on high quality product purchasers and negative externalities on low quality product purchasers. Such a result is consistent with the fact that information undermines brand. If uninformed consumers are skeptical, adverse selection issues arise and market demands may be perfectly inelastic to prices. With elastic demands equilibrium prices may be either distorted downwards or reflect real quality if the share of informed consumers is suffciently high. Therefore, with skeptical consumers firms may want either to signal quality or subsidize information provision.