Insider trading and risk aversion

This paper is a continuous time version of Holden and Subrahmanyam (Economics Letters 44 (1994) 181). The paper extends Kyle (Econometrica 53 (1985) 1315) by introducing risk aversion on the side of the monopolist informed trader and allows for the liquidity traders instantaneous demand to depend on cost of trading, as well as on the risk of the stock. The main result of the paper is that, in equilibrium, the price pressure decreases with time regardless of the elasticity of the liquidity demand function.     

Information‐Hedging Disclosures and Insider Trading

I model the effect of disclosure on the tradeoff between information risk, liquidity risk, and price risk for a well‐informed, risk‐averse insider. Revealing some information before trading decreases the variability of the insider's information advantage and thus reduces his information risk. Disclosure also lowers adverse selection costs for market makers, which reduces the insider's liquidity risk by increasing his trading flexibility. However, disclosure increases price risk for the insider because the price fully reflects the revealed information. The reduction in information and liquidity risks outweigh the rise in price risk when the insider is less risk averse because a less risk‐averse insider's information‐based motive for trading is stronger than his hedging motive. The opposite relation holds when the insider is more risk averse. Therefore, a less (more) risk‐averse insider experiences an increase (decrease) in welfare when he discloses some information before trading. Cost of capital and policy implications are identified.     

The “make or take” decision in an electronic market: Evidence on the evolution of liquidity

This paper uses experimental asset markets to investigate the evolution of liquidity in an electronic limit order market. Our market setting includes salient features of electronic limit order markets, as well as informed traders and liquidity traders. We focus on the strategies of the traders and how these are affected by trader type, characteristics of the market, and characteristics of the asset. We find that informed traders use more limit orders than do liquidity traders. Our main result is that liquidity provision shifts as trading progresses, with informed traders increasingly providing liquidity in markets. The change in the behavior of the informed traders seems to be in response to the dynamic adjustment of prices to information; they take (provide) liquidity when the value of their information is high (low). Thus, a market-making role emerges endogenously in our electronic markets and is ultimately adopted by the traders who are least subject to adverse selection when placing limit orders.     

The effect of sequential information releases on trading volume and price behaviour

This paper examines a two-period setting in which each trader receives a private signal, possibly different, in each period before he trades. The principal objectives are threefold. First, we describe the risky asset demands and price reactions in a noisy rational expectations equilibrium where the time 1 average private signal is not revealed by the price sequence but the time 2 average private signal is. Secondly, we analyse how informed trading volume is affected by the revealed information and supply shocks when pure noise trading volume is uncorrected with observable market variables. Our result indicates that no trade occurs for informed traders when net supply remains fixed across rounds of trade. And, when supply shocks are random, trading volume is induced by the informed and the noise traders, but noise trading is not predictable. Finally, we investigate these properties in the case when pure noise trading volume is correlated with observable market variables. It is shown that no informed trading takes place when there is no supply shock. However, when net supply contains random shocks, trading volume consists of noise and informed trading, both of which can be estimated.     

Trading performance and market efficiency: Evidence from algorithmic trading

In India, National Stock Exchange directly identifies algorithmic trading participation. Algorithmic traders possess intraday market timing skills. Results are not motivated by extreme short-term signals or transitory price trading. Magnitude of market timing performance in cross-sectional group of traders shows that they earn profit across all the cases, and maximize while providing liquidity. Volume-weighted-average-price decomposition analysis reports algorithmic traders earn profits through intraday market timing performance for five-minute and one-minute intervals, and it is higher compared to short-term market timing performance across all trader groups. Order imbalance and price delay regressions show that algorithmic trading significantly improves price efficiency.     

Arbitrage Chains

A privately informed trader will engage in costly arbitrage, that is, trade on his knowledge that the price of an asset is different from the fundamental value if: (1) his order does not move the price immediately to reflect the information; and (2) he can hold the asset until the date when the information is reflected in the price. We study a general equilibrium model in which all agents optimize. In each period, there may be a trader with a limited horizon who has private information about a distant event. Whether he acts on his information, and whether subsequent informed traders act, is shown to depend on the possibility of a sequence or chain of future informed traders spanning the event date. An arbitrageur who receives good news will buy only if it is likely that, at the end of his trading horizon, a subsequent arbitrageur's buying will have pushed up the expected price. We show that limited trading horizons result in inefficient prices, because informed traders do not act on their information until the event date is sufficiently close. We also show that limited horizons can arise because of the cost-carry associated with holding an arbitrage portfolio over an extended period of time.     

Strategic trading and learning about liquidity

Many practitioners point out that the speculative profits of institutional traders are eroded by the difficulty in gauging the price impact of their trades. In this paper, we develop a model of strategic trading where speculators face such a dilemma because of incomplete information about time-varying market liquidity. Unlike the competitive market makers that they trade against, informed traders do not know the distribution of liquidity (“noise”) trades. Instead, they have to learn about liquidity from past prices and trading volume. This learning implies that strategic trades and market statistics such as informational efficiency are path-dependent on past market outcomes. Our paper also has normative implications for practitioners.     

Information, Trading Demand, and Futures Price Volatility

We examine the relation between futures price volatility and trading demand by type of trader in the Standard & Poor's (S&P) 500-stock index futures market. We find that volatility covaries negatively with signed speculative demand shocks but is positively related to signed hedging demand shocks. No significant relation between volatility and demand shocks for small traders is found. Our results suggest that changes in positions of large hedgers destabilize the market, whereas changes in positions of large speculators stabilize volatility. Consistent with models with asymmetrically informed traders, we find that large speculators are likely to possess superior forecasting ability, large hedgers behave like positive feedback traders, and small traders are liquidity traders.     

The Dynamic Properties of Financial‐Market Equilibrium with Trading Fees

We incorporate trading fees into a dynamic, multiagent general‐equilibrium model in which traders optimally decide when to trade. For that purpose, we propose an innovative algorithm that synchronizes the traders. Securities prices are not so much affected by the payment of the fees itself, but rather by the trade‐off that the traders face between smoothing consumption and smoothing holdings. In calibrated examples, the interest rate and welfare decline with trading fees, while risk premia and volatilities increase. Liquidity risk and expected liquidity are priced, leading to deviations from the consumption‐CAPM. With trading fees, capital is slow‐moving, generating slow price reversal.     

A theory of the interday variations in volume, variance, and trading costs in securities markets

In an adverse selection model of a securities market with oneinformed trader and several liquidity traders, we study theimplications of the assumption that the informed trader hasmore information on Monday than on other days. We examine theinterday variations in volume, variance, and adverse selectioncosts, and find that on monday the trading costs and the varianceof price changes are highest, and the volume is lower than onTuesday. These effects are stronger for firms with better publicreporting and for firms with more discretionary liquidity trading.     

Predatory Trading

This paper studies predatory trading, trading that induces and/or exploits the need of other investors to reduce their positions. We show that if one trader needs to sell, others also sell and subsequently buy back the asset. This leads to price overshooting and a reduced liquidation value for the distressed trader. Hence, the market is illiquid when liquidity is most needed. Further, a trader profits from triggering another trader's crisis, and the crisis can spill over across traders and across markets.     

Trading costs, liquidity, and asset holdings

In this article I develop a model that accounts for interdependencebetween trading costs in various asset markets arising fromthe optimizing behavior of liquidity traders. The model suggeststhat noise trading is an important determinant of the liquidityof asset markets and provides a positive theory for diversifiedasset holdings by risk-neutral liquidity traders.     

Do market prices reveal the decision models of sophisticated investors?: Evidence from the laboratory

If security prices are fully revealing, then all public information should be reflected in prices, and unsophisticated traders may be able to learn how various types of information affect security valuation by observing prices. A series of laboratory asset markets was conducted to examine whether unsophisticated traders are able to learn to evaluate publicly released information by trading with and observing trades made by a sophisticated trader who knows the valuation implications of the information. We find that unsophisticated traders who participate in an asset market with a sophisticated trader show significant improvement in their ability to use public information on a subsequent price estimation task. Conversely, a control group consisting only of unsophisticated traders shows no improvement. We conclude that market prices convey the sophisticated trader’s private information in a manner that permits unsophisticated investors to learn the stock price implications of a public information release.     

Dancing in the dark: post-trade anonymity,liquidity and informed trading

We analyze the impact of post-trade anonymity on liquidity and informed trading in an order driven stock market. The German stock market introduced the Central Counterparty (CCP) in March 2003 for German equities traded on its anonymous electronic trading platform Xetra leading to a major change in its existing transparency regime. Before the introduction trader IDs were revealed to the counterparties of a trade, with the introduction of the CCP even after the transaction the traders remain anonymous. Previous theoretical and empirical research documents that pre-trade anonymity results in increased liquidity, while results on post-trade anonymity are mixed. We find a significant increase in liquidity measured through a reduction of 25% in implicit transaction costs. We also document that the arrival rate of informed traders is reduced in the anonymous setting. Following recent findings of Bloomfield et al. (J Finan Econ 75:165–199, 2005) that informed traders take on the role of liquidity providers we interpret our findings as indication that informed traders change their behavior in providing liquidity more aggressively in an anonymous environment.     

基于面板数据的我国知情交易与股价信息含量研究

知情交易概率是指知情交易委托单占总交易委托单的比重,用于度量我国知情交易强度。R2代表公司回报率能被市场回报率解释的程度,R2越大,股价信息含量越低。在以往的研究基础上,利用面板数据来考察知情交易概率与股价信息含量的关系,发现知情交易概率越低,R2越高,股价信息含量越低。在控制了流动性与部分公司财务指标后,实证结果依然显示我国股价信息含量与知情交易概率存在正相关关系,说明我国知情交易者进行交易时,更有利于公司特质信息进入股票价格。     

Liquidity Trading in Market Microstructure Theory

Liquidity trading is an important component of market microstructure models. In most cases, its role is primarily to ensure existence of equilibrium and therefore that trading occurs among asymmetrically informed agents. While most market microstructure models allege that agents trade based upon rational expectations, the rationality of the type of liquidity trading assumed in these models remains to be verified. Specifically, liquidity traders are often assumed to submit price-inelastic orders for reasons exogenous to the model at hand. But whether price-inelastic trading is consistent with rational utility maximizing behavior remains to be shown.     

Strategic trading, asymmetric information and heterogeneous prior beliefs

We develop a multi-period trading model in which traders face both asymmetric information and heterogeneous prior beliefs. Heterogeneity arises because traders agree to disagree on the precision of an informed trader's private signal. In equilibrium, the informed trader smooths out her trading on asymmetric information gradually over time, but concentrates her entire trading on heterogeneous beliefs toward the last few periods. As a result, the model's volume dynamics are consistent with the U-shaped intraday pattern at the close. Furthermore, the model predicts a positive autocorrelation in trading volume, and a positive correlation between trading volume and contemporaneous price volatility.     

Multimarket trading and market liquidity

When a security trades at multiple locations simultaneously,an informed trader has several avenues in which to exploit hisprivate information. The greater the proportion of liquiditytrading by 'large' traders who can split their trades acrossmarkets, the larger is the correlation between volume in differentmarkets and the smaller is the informativeness of prices. Weshow that one of the markets emerges as the dominant locationfor trading in that security. When informed traders can usetheir information for more than one trading period, the timelyrelease of price information by market informed traders expectto make subsequently at other locations. Markets makers, competingto offer the lowest cost of trading at their location, consequentlydeter informal trading by voluntarily making the price informationpublic and by 'cracking down' on insider trading.     

Market making, prices, and quantity limits

This article develops a model of spread and depth setting underasymmetric information where the equilibrium depth is proportionallymore sensitive than the spread to changes in the degree of informationasymmetry. The analysis uses a one-period model in which a risk-neutral,monopolistic market maker faces a price-sensitive liquiditytrader and a better informed trader who is alternatively riskneutral and risk averse. The equilibrium depth can take valuesranging from 0 to infinity, depending on the information asymmetry,the asset volatility, and the strength of the liquidity demand,while the spread remains positive and finite.     

Optimal Dynamic Order Submission Strategies in Some Stylized Trading Problems

This study derives optimal dynamic order submission strategies for trading problems faced by three stylized traders: an uninformed liquidity trader, an informed trader and a value-motivated trader. Separate solutions are obtained for quote- and order-driven markets. The results provide practicable rules for how to trade small orders and how to manage traders. Transaction cost measurement methods based on implementation shortfall are proven to dominate other methods.
Since investors demand liquidity when they submit market orders and supply liquidity when they submit limit orders, the results improve our understanding of market liquidity. In particular, the models illustrate the role of time in the search for liquidity by characterizing the demand for and supply of immediacy.