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.     

Volume, Volatility, Price, and Profit When All Traders Are Above Average

People are overconfident. Overconfidence affects financial markets. How depends on who in the market is overconfident and on how information is distributed. This paper examines markets in which price-taking traders, a strategic-trading insider, and risk-averse marketmakers are overconfident. Overconfidence increases expected trading volume, increases market depth, and decreases the expected utility of overconfident traders. Its effect on volatility and price quality depend on who is overconfident. Overconfident traders can cause markets to underreact to the information of rational traders. Markets also underreact to abstract, statistical, and highly relevant information, and they overreact to salient, anecdotal, and less relevant information.     

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.     

The price discovery role of day traders in futures market: Evidence from different types of day traders

Using proprietary account-level transaction data in the futures market where day traders are self-declared ex ante, this study investigates whether day traders enhance price discovery at the market level. From a natural classification of day traders, we find that heterogeneous day traders have differential effects on price discovery. Self-declared day traders, who benefit from low margin requirement, do not improve price discovery measured by information share. In contrast, non-declared traders, who are not self-declared as day traders, improve price discovery. Their positive impacts on price discovery are particularly significant during periods of high volatility and arrival of new information. Overall, a margin stimulating policy may encourage more day trading, but may also attract overconfident investors, especially inexperienced ones, and who do not enhance price discovery.     

期货市场的交易量与价格波动

本文检验了美国期货市场WTI原油、S＆P500指数和10年期国债品种的日内、日间价格波动与日内交易量、隔日交易量之间的关系,发现预期的日内和隔日交易量都有平抑期货市场价格波动的作用,非预期的隔日交易量与期货价格波动之间有正相关关系,非预期的目内交易量对价格波动的影响不显著。从信息对称性的角度分析,预期的交易量中含有更多信息,能抑制期货价格的偏离;非预期的交易量主要由信息反馈者提供,他们往往对期货价格的变动做出过度反应,从而加剧价格波动。     

Reputation and interdealer trading: a microstructure analysis of the Treasury Bond market

Trading generates not only information about the payoff of the assets traded, but also information about the traders themselves. Over time this information creates reputation. By using a unique dataset on the Treasury bond market, we derive a measure of reputation. This is then used to group dealers on the basis of their reputation and to analyze how they react to the reputation of other dealers. We show that the same type of trade, on the same asset, in the same market can generate different volume and volatility patterns depending on the type of dealers originating it. We also identify the “salient traders”. These traders, even if they do not originate the biggest volume of trade, have the highest impact on the market. These results have strong implications in terms of forecastability of future returns, volatility and overall trading volume because they show that most of the explanatory power of trades is due to salient traders.     

Momentum,Reversal, and Uninformed Traders in Laboratory Markets

We report the results of three experiments based on the model of Hong and Stein (1999) . Consistent with the model, the results show that when informed traders do not observe prices, uninformed traders generate long‐term price reversals by engaging in momentum trade. However, when informed traders also observe prices, uninformed traders generate reversals by engaging in contrarian trading. The results suggest that a dominated information set is sufficient to account for the contrarian behavior observed among individual investors, and that uninformed traders may be responsible for long‐term price reversals but play little role in driving short‐term momentum.     

Information, speed vs. cost trade-offs, and order routing decisions in U.S. equity markets

Prior research indicates that both execution speed and cost are important to traders, but that these two dimensions of execution quality are negatively related across U.S. equity markets. In our paper, we examine how U.S. equity traders, who are (un)informed about future price changes, trade-off between speed and cost in their order-routing decisions. We find that informed traders are more likely to choose trading systems that allow them to trade-off lower cost for faster speed; whereas, uninformed traders are more likely to choose trading systems that allow them to sacrifice speed for lower costs. Our results indicate that traders have varying preferences for the different dimensions of execution quality based on their information levels. These differences subsequently influence order-routing decisions.     

Differences of opinion make a horse race

A model of trading in speculative markets is based on differencesof opinion among traders. Our purpose is to explain some ofthe empirical regularities that have been documented concerningthe relationship between volume and price and the time-seriesproperties of price and volume. We assume that traders sharecommon prior beliefs and receive common information but differin the way in which they interpret this information. Some resultsare that absolute price changes and volume are positively correlated,consecutive price changes exhibit negative serial correlation,and volume is positively autocorrelated.     

On the hidden side of liquidity

This article deals with the informativeness of iceberg orders, also known as hidden limit orders (HLOs). Namely, we analyze how the market reacts when the presence of hidden volume in the limit order book is revealed by the trading process. We use high-frequency book and transaction data from the Spanish Stock Exchange, including a large sample of executed HLOs. We show that just when hidden volume is detected, traders on the opposite side of the market become more aggressive, exploiting the opportunity to consume more than expected at the best quotes. However, neither illiquidity nor volatility increases in the short term. Furthermore, the detection of hidden volume has no relevant price impact. Overall, our results suggest that market participants do not attribute any relevant information content to the hidden side of liquidity.     

The Effect of Sequential Information Arrival on Asset Prices: An Experimental Study

A complete understanding of security markets requires a simultaneous explanation of price behavior, trading volume, portfolio composition (ie., asset allocation), and bid-ask spreads. In this paper, these variables are observed in a controlled setting—a computerized double auction market, similar to NASDAQ. Our laboratory allows experimental control of information arrival—whether simultaneously or sequentially received, and whether homogeneous or heterogeneous. We compare the price, volume, and share allocations of three market equilibrium models: telepathic rational expectations, which assumes that traders can read each others minds (strong-form market efficiency); ordinary rational expectations, which assumes traders can use (some) market price information, (a type of semi-strong form efficiency); and private information, where traders use no market information. We conclude 1) that stronger-form market models predict equilibrium prices better than weaker-form models, 2) that there were fewer misallocation forecasts in simultaneous information arrival (SIM) environments, 3) that trading volume was significantly higher in SIM environments, 4) and that bid-ask spreads widen significantly when traders are exposed to price uncertainty resulting from information heterogeneity.     

Prospect theory and the effectiveness of price limits

Assuming that traders are risk-neutral, Brennan (1986) shows that price limits are effective in improving the efficiency of futures contracts with limited accessibility to information because they obscure the exact loss when they are triggered. However, Brennan's (1986) model fails to explain why price limits also exist in contracts with abundant information like those of financial futures. We show that when traders are loss-averse, the effectiveness of price limits is strengthened even in the presence of precise information. Thus, our analysis provides a theoretical foundation explaining why price limits can be useful when market participants are not fully rational.     

Trading Volume, Information Asymmetry, and Timing Information

This paper investigates trading volume before scheduled and unscheduled corporate announcements to explore how traders respond to private information. I show that cumulative trading volume decreases inversely to information asymmetry prior to scheduled announcements, while the opposite relation holds for volume after the announcement. In contrast, trading volume before unscheduled announcements increases dramatically and shows little relation to proxies for information asymmetry. I investigate the behavior of market makers and find that they act appropriately by increasing price sensitivity before all announcements, implying that they extract timing information from their order books.     

Asymmetric Volume‐Return Relation and Concentrated Trading in LIFFE Futures

This study demonstrates that intraday volume and return on LIFFE interest rate and currency futures exhibit an asymmetric volume‐return relationship characterised by significantly larger volume associated with negative returns than with non‐negative returns. This finding is unlike the stylised asymmetric relation often observed in equity markets, where the volume on price rise is larger than the volume on price decline. The asymmetric relationship in LIFFE futures is also found to be dynamic as the direction of asymmetry can reverse during the day. It has been argued in the past that a costly short sale restriction that requires a higher transaction cost on a short position than on a long position is responsible for the asymmetric effect in equity markets. Since such a restriction is absent in futures markets, they should not exhibit any asymmetric volume behaviour. Based on the results of this research, the costly short sale hypothesis is rejected. An alternative explanation of the asymmetric relation observed in futures is presented based on recent information models that take into consideration asymmetrically‐informed traders, their dispersion of beliefs, quality and quantity of the information signal, and how the traders process it. The paper also confirms a strong U‐shape trading pattern in 15‐minute volume, but no such pattern is identified in intraday returns.     

The Determinants of Execution Costs in Short‐Term Money Markets

Prior research attributes the observed negative relation between execution costs and trade size in opaque markets to two factors—information asymmetry and broker‐client relationships. We provide evidence that a trader's ex ante transaction price information and the relationship traders have with their brokers are both significant determinants of a trader's execution costs in an opaque market; however, traders who establish strong relationships with their brokers will achieve a greater reduction in execution costs than traders with ex ante transaction price information. We also find evidence that trade size has little explanatory power after controlling for a trader's ex ante transaction price information and broker‐client relationships.     

Microstructure and Ambiguity

A goal for stock exchanges is to increase participation by firms and investors. We show how specific features of the microstructure can reduce perceived ambiguity, and induce participation by both investors and issuers. We develop a model with sophisticated traders, who we view as expected utility maximizers with rational expectations, and unsophisticated traders, who we view as rational traders facing ambiguity about the payoffs to participating in the market. We show how designing markets to reduce ambiguity can benefit investors through greater liquidity, exchanges through greater volume, and issuing firms through a lower cost of capital.     

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.     

The behavior of risky asset prices in a symmetric least squares learning environment

This paper examines the dynamics of asset prices in a heterogeneous market. Traders are made up of learners who possess limited information and use limited models for predicting the future. The market also includes noise traders in the sense of Black, along with liquidity traders. Learners revise their prediction equations using least squares learning as defined by Marcet and Sargent. We derive the equilibrium price process and show how convergence is obtained. The price process is shown to have a number of interesting properties that are consistent with propositions outlined by Black. Numerical calculations for several examples illuminate how learning takes place in the model.     

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.     

Trading frequency and the efficiency of price discovery in a non-dealer market

The increasing popularity of non-dealer security markets that offer automated, computer-based, continuous trading reflects a presumption that institutionally-set trading sessions are economically obsolete. This theoretical paper investigates the effect of the trading frequency, a key feature of the trading mechanism, on the efficiency of price discovery in a non-dealer market. By tracing the market pricing error to the correlation structures of arriving information and pricing errors of individual traders, the effect of diverging expectations on error-based and overall return volatility is isolated. The analysis reveals that, due to a portfolio effect, an increase in the trading time interval has contradictory effects on the portion of return volatility stemming from pricing errors. The greater accumulation of information increases error-based return volatility, but the greater volume and number of traders per session have the opposite effect. The net effect on overall return volatility can go either way. It is found that the return volatility of heavily traded securities is likely to be minimized under continuous trading, but that of thinly traded securities may be minimized under discrete trading at moderate time intervals. The latter is more likely to occur the greater is the divergence of expectations among traders. These findings challenge the presumption that automated continuous trading in a non-dealer market is more efficient than discrete trading for all securities, regardless of trading volume. The findings are applicable to all economies, but have special importance for developing countries where typically a single market is dominated by small issues and a low volume of trade. As a by-product of the analysis, it is shown how to correct the biased estimate of inter-session price volatility when observations are less frequent than the trading sessions themselves.