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.     

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 When Agents Forecast the Forecasts of Others

We analyze a multi-period model of trading with differentially informed traders, liquidity traders, and a market maker. Each informed trader's initial information is a noisy estimate of the long-term value of the asset, and the different signals received by informed traders can have a variety of correlation structures. With this setup, informed traders not only compete with each other for trading profits, they also learn about other traders' signals from the observed order flow. Our work suggests that the initial correlation among the informed traders' signals has a significant effect on the informed traders' profits and the informativeness of prices.     

Should short-term speculators be taxed,or subsidised?

Summary This paper explores the welfare implications of a securities transaction tax when long-term information contained in stock prices can improve resource allocation but speculators have short horizon objectives. Speculators can trade on information of differing time horizons and profit maximizing firms can use long-term information contained in stock prices to improve their investment decisions. The model takes full account of the effect of a tax on market liquidity and welfare for all market participants. Surprisingly, a subsidy on short-term speculation can increase the amount of equilibrium trade on long-horizon information. This is because short-term informed trade exerts a positive externality over long-term informed trade when speculators have a short planning horizon. The cost of paying the subsidy may be smaller than the gain in firm value, while no trader is made worse off.This paper is a revised version of chapter 4 of my Ph.D. dissertation written at the European University Institute. I wish to thank Paolo Battigalli, James Dow, Thierry Foucault, Rainer Kiefer, Matt Spiegel, Erik Theissen, the co-editor and two anonymous referees for helpful comments. I would also like to thank audiences at the workshop of the ESSFM Gerzensee and EFA Annual Meetings 2000.     

Market Orders and Market Efficiency

This work compares a dealer market and a limit-order book. Dealers commonly observe order flow and collect information from multiple market orders. They may be better informed than other traders, although they do not earn rents from this information. Dealers earn rents as suppliers of liquidity, and their decisions to enter or exit the market are independent of the degree of adverse selection. Introduction of a limit-order book lowers the execution-price risk faced by speculators and leads them to trade more aggressively on their information. Introduction of the book also lowers dealer profits, but increases the informational efficiency of prices.     

The Effects of Analysts’ Herding on Traders: Evidence from the Taiwan Stock Market

The primary aim of this study is to carry out an investigation into the effects of analysts’ herding on different types of traders in Taiwan stock market. Our empirical results reveal that smaller traders are more readily affected by analyst herding, essentially as a result of their lack of experience and their lack of access to relevant information sources, which leads to them reacting directly to the central point of the recommendations made by the analysts. Our findings also reveal that both small and large traders are affected by analyst herding in the recommendations provided by the analysts relating specifically to buying. As for the evidence on analyst herding in recommendations relating to selling, larger traders are invariably found to have made use of their informational advantages to act in advance of such recommendations.     

Institutional ownership changes and returns around analysts’ earnings forecast release events: Evidence from Taiwan

Traditional data sources do not have institutional holding data on a daily basis. Because of this, most prior empirical studies of institutional herding have focused on quarterly or annual data. The problem, however, with using quarterly or annual data on institutional holdings is that these data may not reveal institutional herding if it occurs over a shorter time interval. For this study, we make use of data from the Taiwan Stock Exchange (TSE). Unlike traditional data sources, the TSE provides daily institutional holdings information. The use of this detailed data allows us to make more interesting analysis and inferences. In this study, we examine the relationship between institutional ownership changes and returns localized around analysts’ earnings forecast release events. Analysis of institutional ownership and return data around the earnings release event allows us to investigate institutional herding and feedback behavior in a different level. Our major results are as follows: (1) there exists a relation between company specific attributes and institutional herding, (2) observed changes in institutional ownership and contemporaneous return are mainly the results of inter-day price impact of herding, (3) institutional investors show evidence of being informed traders in buying but not selling.     

Rational expectations equilibrium with uncertain proportion of informed traders

This paper introduces uncertainty regarding the proportion of informed traders in a rational expectation equilibrium model with asymmetric information. The proportion uncertainty dramatically changes the properties of the resulting equilibrium. First, it may generate multiple nonlinear rational expectations equilibria, which can help explain the excessive volatility of stock prices. Second, the expected price informativeness is a non-monotonic function of the proportion of informed traders, which suggests that the traders will have more incentive to become informed as the proportion of informed traders gets larger.     

Glued to the TV: Distracted Noise Traders and Stock Market Liquidity

In this paper, we study the impact of noise traders’ limited attention on financial markets. Specifically, we exploit episodes of sensational news (exogenous to the market) that distract noise traders. We find that on “distraction days,” trading activity, liquidity, and volatility decrease, and prices reverse less among stocks owned predominantly by noise traders. These outcomes contrast sharply with those due to the inattention of informed speculators and market makers, and are consistent with noise traders mitigating adverse selection risk. We discuss the evolution of these outcomes over time and the role of technological changes.     

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.     

Does a scopic regime produce conformism? Herding behavior among trade leaders on social trading platforms

Social trading platforms (STPs) are transparent online markets governed by a scopic regime, where order flow is publicly disclosed and participants are subject to constant reciprocal scrutiny. Participants on STPs can be categorized into trade leaders and copiers, where the former execute unique trades and manage the funds allocated to them by the latter in return for compensation. Given limited individual capacity and the competition to attract copiers, we investigate whether the scopic regime produces excess and perpetual conformism among trade leaders. Using data from a popular STP, and from an anonymous traditional foreign exchange broker, we show that the scopic regime produces excess levels of herding. Under the scopic environment, we find that herding is high when market information is scarce, which is evidence of herding due to informational cascades. We find herding to be relatively low among risk-seeking trade leaders, which may be a sign of overconfidence. Herding is high for larger trades, suggesting that traders herd to avoid the disappointment associated with underperforming on large positions. Finally, we show that herding in the scopic environment persists at much higher levels compared to traditional environments. Our findings indicate that exposure to a scopic information-rich environment augments the limitations and personal biases of individual traders, thus producing excess and perpetual herding.     

Futures Commitments and Commodity Price Jumps

We examine the relationship between the commitments of three of the largest groups of futures traders and the abnormal price movements in five agricultural commodities. The general evidence suggests that the commitments of futures traders have been increasing over time, whereas the frequency of price jumps have not. Regression results indicate a negative relationship between price jumps and the commitments of speculators and small traders. There is also evidence of a negative relationship between the number of speculators and cash market volatility, consistent with a host of speculation-based theories.     

Financial Speculators' Underperformance: Learning, Self-Selection, and Endogenous Liquidity

We develop an equilibrium model of learning by rational traders to reconcile several empirical regularities: Cross sectionally, most individual speculators lose money; large speculators outperform small speculators; past performance positively affects subsequent trade intensity; most new traders lose money and cease speculation; and performance shows persistence. Learning from trading generates substantial endogenous liquidity, reducing bid–ask spreads and the impact of exogenous liquidity shocks on asset prices, but amplifying the effects of real shocks. Introducing slightly overconfident traders increases bid–ask spreads, hurting all traders. Finally, behavioral theories cannot reconcile all of these empirical regularities.     

Financial crises in efficient markets: How fundamentalists fuel volatility

When a financial crisis breaks out, speculators typically get the blame whereas fundamentalists are presented as the safeguard against excessive volatility. This paper proposes an asset pricing model where two types of rational traders coexist: short-term speculators and long-term fundamentalists, both sharing the same information set. In this framework, excess volatility not only exists, but is actually fueled by fundamental trading. Consequently, efficient markets are more volatile with a few speculators than with many speculators. Regulators should therefore be aware that efforts to limit rational speculation might, surprisingly, end up increasing volatility.     

Profitability of return and sentiment-based investment strategies in US futures markets

Our study adds to the literature by providing initial evidence on the interaction between short-horizon return predictability and investors’ sentiment by traders’ types on US commodity futures market. We find that the short-term contrarian profit is more associated with an increase rather than a decrease in hedgers’ sentiment. However, the interaction between lagged return and past change in speculators’ sentiment illustrates that the short-term contrarian profit is more associated with a decrease rather than an increase in sentiment. Based on behavioral finance theories, we conclude that hedgers behave like irrational traders while speculators behave like rational ones. Using Chou et al. (2007) decomposition, our results confirm the obtained relations between change in trader's sentiment and the overreaction. By expanding this decomposition, we find that the winners’ portfolio tends to more overreact with futures specific information. Also, the cross-autocorrelation between winners and losers and between losers and winners can represent another source of contrarian profits.     

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.     

The generality of spurious predictability

Previous empirical work has documented significant predictability (non-zero cross autocorrelations) in short-term security returns. Extant theoretical papers have shown that these cross autocorrelations can arise due to partial impounding of information in securities whose returns are driven by a common factor. In this paper, we show that non-zero cross autocorrelation in security returns can arise under weaker conditions than is generally known. We demonstrate that the existence of cross autocorrelations crucially depends on the information structure of informed traders. Thus, a common factor in security returns is neither sufficient nor necessary. Any one of the following conditions on the information structure can generate non-zero cross autocorrelations:

(1) existence of an informed trader with information relevant to two securities;

(2) correlation in the signal of informed traders with information relevant to different securities; or

(3) correlation in uninformed trading.

These cross autocorrelations are then shown to be spurious. That is, traders without any private information cannot make positive trading profit by exploiting cross autocorrelations.     

Can margin traders predict future stock returns in Japan?

A growing body of literature suggests that investor sentiment affects stock prices both at the firm level and at the market level. This study examines the relationship between investor behavior and stock returns focusing on Japanese margin transactions using weekly data from 1994 to 2003. Margin trading is dominated by individual investors in Japan. In analysis at the firm level, we find a significant cross-sectional relationship between margin buying and stock returns. Both market-level and firm-level analyses show that margin buying traders follow herding behavior. They seem to follow positive feedback trading behavior for small-firm stocks and negative feedback trading behavior for large firm stocks. Our results show that information about margin buying helps predict future stock returns, especially for small-firm stocks at short horizons. The predictive power does not diminish even after controlling for firm size and liquidity.     

CAN INEFFICIENT TRADERS CREATE VALUE?

I examine the aggregate expected profit generated by informed traders of diverse ability in a competitive market. I assume that efficient traders get perfect information on asset values whereas inefficient traders get noisy information. In the presence of order size restrictions, I show that the aggregate expected profit generated by efficient and inefficient traders together can be higher than that generated by efficient traders alone. Thus, inefficient traders can create value in a constrained trading environment.     

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.