Price manipulation in an experimental asset market

We analyze in the laboratory whether an uninformed trader is able to manipulate the price of a financial asset by comparing the results of two experimental treatments. In the benchmark treatment, 12 subjects trade a common value asset that takes either a high or a low value. Only three subjects know the actual value of the asset while the market is open for trading. The manipulation treatment is identical to the benchmark treatment apart from the fact that we introduce a computer program as an additional uninformed trader. This robot buys a fixed number of shares in the beginning of a trading period and sells them again afterwards. Our main result shows that the last contract price is significantly higher in the manipulation treatment if the asset takes a low value and that private information is very well disseminated by both markets if the value of the asset is high. Finally, even though this simple manipulation program loses money on average, it is profitable in some instances.     

Manipulation and the Allocational Role of Prices

It is commonly believed that prices in secondary financial markets play an important allocational role because they contain information that facilitates the efficient allocation of resources. This paper identifies a limitation inherent in this role of prices. It shows that the presence of a feedback effect from the financial market to the real value of a firm creates an incentive for an uninformed trader to sell the firm's stock. When this happens the informativeness of the stock price decreases, and the beneficial allocational role of the financial market weakens. The trader profits from this trading strategy, partly because his trading distorts the firm's investment. We therefore refer to this strategy as manipulation . We show that trading without information is profitable only with sell orders, driving a wedge between the allocational implications of buyer and seller initiated speculation, and providing justification for restrictions on short sales.     

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.     

Speculative dynamics

We develop a method for solving for equilibrium outcomes in stationary strategic settings in which speculators are informationally large and understand how their actions affect the information content of prices. This allows us to characterize speculation by institutional investors who receive private long-lived information on a recurring basis, and trade strategically. When the underlying asset value process has a stationary autoregressive structure, we develop a contraction mapping argument to solve for the stationary linear equilibrium. We derive analytically and numerically how the characteristics of private information—its quantity, persistence and correlation, and division among speculators—affect trading profits, pricing and trading strategies. Our central finding is that what matters for equilibrium outcomes are the most recent signals that speculators receive. Speculators trade so much more aggressively on new information than old that the bulk of their profits come from their two or three most recent private signals. Trading on past prices drops off faster yet; effectively only the most recent price matters.     

工业园区废弃物交易生态协作激励机制

在分析工业园区废弃物交易存在资产专用性和不确定性等问题的基础上,通过构建园区废弃物交易生态协作收益模型,分别探讨了社会最优条件下、单期交易条件下和关系契约条件下有助于废弃物交易双方生态协作的最优激励机制安排。研究结果表明:资产专用性和不确定性等导致单期交易下生态协作存在效率损失,此时根据生产效率分配协作租金可最大程度地减少生态协作效率损失;关系契约推动了生态协作效率的提升,利用企业可通过隐藏废弃物在利用环节的价值增值信息以及调节奖励支付规则等获得社会最优条件下的生态协作收益;废弃物交易双方越关注未来的预期收益,废弃物交易中的协作程度越高,废弃物交易双方获取的生态协作收益就越大;废弃物再利用的成本越高,越需要交易双方进行长期协作,越需要对园区进行政策干预。     

Communication in financial markets with several informed traders

This paper investigates the incentives for informed traders in financial markets to reveal their information truthfully to the public. In the model, a subset of traders receive noisy signals about the value of a risky asset. The signals are composed of a directional component (“high” vs. “low”) as well as a precision component that represents the quality of the directional component. Between trading periods, the informed agents make public announcements to the uninformed traders. With a sufficiently large number of informed traders, an equilibrium exists in which the directional components are credibly revealed, but not the precision components. Even though the informed traders retain some of their rivate information, the post-communication estimate of the asset value converges in probability to the full-information estimate as the number of informed traders increases. The paper is based on a chapter of my Ph.D. thesis at the University of Western Ontario and was circulated previously under the title “Public Communication Devices in Financial Markets.” I thank my dissertation committee Arthur Robson, Hari Govindan, and Al Slivinski for their guidance and support. I also thank Murali Agastya, Roland Benabou, Philippe Grégoire, Rick Harbaugh, Mike Peters, an anonymous referee and an associate editor, and seminar participants at various universities and conferences at which this paper was presented.     

Abuse of EU Emissions Trading for Tacit Collusion

In this paper, we show that loopholes in EU emissions trading law foster tacit collusion that impacts oligopolistic product markets. The abuses originate from the covert misuse of EU emissions trading institutions, such as pooling or project-based mechanisms. We analyse two types of these loopholes by means of game theoretical methods to show how oligopolistic firms establish output restrictions, even if those firms are price takers on the~permit market (which might actually be the case for the majority of obligated firms in the EU). The identified misuse of emissions trading law increases firms’ profits, decreases the consumers’ surplus and has negative effects on social welfare for specified parameter ranges. Consequently, public authorities should not allow emissions trading’s overall good reputation—based upon its efficient abatement of pollution—to blind them to options in European emissions trading legislation that would eventually restrict competition.      

Misperceiving the value of information in predicting the performance of others

Economic models typically allow for “free disposal” or “reversibility” of information, which implies non-negative value. Building on previous research on the “curse of knowledge” we explore situations where this might not be so. In three experiments, we document situations in which participants place positive value on information in attempting to predict the performance of uninformed others, even when acquiring that information diminishes their earnings. In the first experiment, a majority of participants choose to hire informed—rather than uninformed—agents, leading to lower earnings. In the second experiment, a significant number of participants pay for information—the solution to a puzzle—that hurts their ability to predict how many others will solve the puzzle. In the third experiment, we find that the effect is reduced with experience and feedback on the actual performance to be predicted. We discuss implications of our results for the role of information and informed decision making in economic situations. Electronic Supplementary Material Supplementary material is available in the online version of this article at http://dx.doi.org/10.1007/s10683-006-9128-y. JEL Classification C91, D83     

Informed trade,uninformed trade and stock price delay

The probability of informed trading (PIN), a measure of information-based trading risk, has been broadly applied to empirical studies on asset pricing. However, it is still controversial whether PIN measures exclusively the risk of firm-specific private information or it also captures the private interpretation of market wide public information. This article examines the relevance of PIN to the delayed response of stock prices to market-wide information. We find that PIN significantly explains individual stock price delay even controlling for size, liquidity and risk, and low-PIN stock prices adjust to market information more rapidly not only because of a notably high level of informed trading but also an even much higher level of uninformed trading. Our findings support the notion that PIN also captures the private skilled interpretation of public common factor information by sophisticated investors, and provide new empirical evidence on how information-based trading affects the speed at which stock prices adjust to information.     

Asset trading volume in a production economy

Judd et al. (J Finance 63: 2203–2217, 2003) show that the stationary Lucas tree model cannot generate nontrivial asset trading: Heterogenous agents will optimally choose a fixed portfolio after initial rebalancing. This paper explores asset trading volume in production economies with heterogeneous agents and dynamically complete market structures. We establish a recursive version of the Negishi approach to prove the existence of a competitive equilibrium. Furthermore, we develop a general method to solve for equilibrium portfolios in production economies within a fairly general set of complete market structures. We thus establish the theoretical reasons why production economies in general generate a nontrivial volume of asset trading even if heterogeneity of the agents is kept to a minimum. We would like to thank W. Brock, D. DeJong and, especially, H. Ennis for comments and suggestions. We also thank seminar participants at Di Tella and San Andrés Universities (Argentina), the Institute for Advanced Studies (Austria), SED Meetings 2005 (Budapest) and SAET Conference 2005 (Vigo).     

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.     

Don’t let your robots grow up to be traders: Artificial intelligence, human intelligence, and asset-market bubbles

Researchers who have examined markets populated by “robot traders” have claimed that the high level of allocative efficiency observed in experimental markets is driven largely by the “intelligence” implicit in the rules of the market. Furthermore, they view the ability of agents (artificial or human) to process information and make rational decisions as unnecessary for the efficient operation of markets. This paper presents a new series of market experiments that show that markets populated with standard robot traders are no longer efficient if time is a meaningful element, as it is in all asset markets. While simple two-season markets with human subjects reliably converge to an efficient equilibrium, markets with minimally intelligent robot traders fail to attain this equilibrium. Instead, these markets overshoot the equilibrium and then crash below it. In addition to firmly establishing the role of trader intelligence in asset-market equilibrium, these experiments also provide insights into why bubbles and crashes are consistently observed in many asset-market laboratory experiments using human subjects.     

Geographic patterns of trading profitability in Xetra

Transaction data from the electronic trading system Xetra of the German Security Exchange is used to explore the relationship between trader location and trading profitability. The non-discriminatory nature of the electronic trading system and its wide international adoption allows interesting conclusions about the information geography of international equity trading. We use spectral analysis to examine trading profitability over intraday, intraweek, and intraquarter inventory cycles. Proprietary trader accounts reveal the underperformance of foreign traders at all three trading horizons. Our analysis confirms the hypothesis of financial market segmentation due to international information barriers.     

Two-period trading sentiment asset pricing model with information

We present a dynamic asset pricing model with investor sentiment and information, which shows that the investor sentiment plays a systematic and important role in the asset prices and the information is gradually incorporated into prices. The model has an analytical solution to the sentiment equilibrium price. We find that sentiment trading quantity not only increases the market liquidity, but also causes the asset prices' overreaction if the intensity of sentiment demand is more than a constant value. Therefore, the continuing overreactions result in a short-term momentum and a long-term reversal. The model could offer a partial explanation to some financial anomalies such as price bubbles, high volatility, asset prices' overreaction and so on.     

The Neural Inhibition of Learning Increases Asset Market Bubbles: Experimental Evidence

The authors tested a leading theory of bubble formation, insufficient learning, in a laboratory asset market using a drug, Naltrexone, which inhibits reinforcement learning. We found that asset price bubbles in Naltrexone sessions were larger compared with placebo sessions, averaging 60% higher in amplitude and 77% larger in the deviation from fundamental value in the final 12-period trading round. There was no difference between conditions in understanding of the trading rules, overconfidence, or confusion. Participants on Naltrexone appeared unable to determine appropriate trading strategies as prices changed. The findings indicate that specific neural mechanism of reinforcement learning is involved in the formation of asset market bubbles.     

Do Speculative Stocks Lower Prices and Increase Volatility of Value Stocks?

The influence of speculative stocks on value stocks is examined through a set of economics experiments. The speculative asset is designed to model a company involved in a rapidly growing market that will be saturated at some unknown point. Using a control experiment where both assets are similar value stocks, we find statistical support for the assertion that the presence of a speculative stock increases the volatility and diminishes the price of the value stock. In addition, the temporal minimum price of the value stock during the last phase of the experiment is lower in the presence of the speculative stock (when the trading price of the speculative asset is declining sharply). These results indicate that an overreaction in the speculative stock tends to divert investment capital away from other assets. An examination of the relative magnitude of monthly closing price changes confirm strong correlations between the Dow Jones Average and the more speculative Nasdaq index during the time period 1990 to 2001 and particularly during the two years prior to the peak in March 2000 (0.72 correlation) and the March 2000 to August 2001 decline (0.79 correlation). Supplementary experiments using independent (or legally separate) markets trading the same asset show that a higher price in one market does not lead to a higher one in the other.     

Consumption,wealth and business cycles in Germany

This paper studies the long-run relationship between consumption, asset wealth and income—the consumption–wealth ratio—based on German data from 1980 to 2003. We find that departures from this long-run relationship mainly predict adjustments in income. The German consumption–wealth ratio also contains considerable forecasting power for a range of business cycle indicators, including the unemployment rate. This finding is in contrast to earlier studies for some of the Anglo-Saxon economies that have shown that the consumption–wealth ratio reverts to its long-run mean mainly through subsequent adjustments in asset prices. While the German consumption wealth ratio contains little information about future changes in German asset prices, we report that the U.S. consumption–wealth ratio has considerable forecasting power for the German stock market. One explanation of these findings is that in Germany—due to structural differences in the financial and pension systems—the share of publicly traded equity in aggregate household wealth is much smaller than in the Anglo-Saxon countries. We discuss the implications of our results for the measurement of a potential wealth effect on consumption. The views expressed in this paper are those of the authors and do not reflect the position of the Deutsche Bundesbank. We gratefully acknowledge comments and suggestions from an anonymous referee as well as from Heinz Herrmann, Helmut Lütkepohl, the editor, Baldev Raj, Burkhard Raunig, Monika Schnitzer, Harald Uhlig and Christian Upper. We also benefitted from comments by seminar participants at the ECB, the Deutsche Bundesbank, the CESifo Macro, Money and International Finance Area Conference 2005, the EEA 2005 annual congress and at the 2005 IAEA Meetings. Last but not least, we would like to thank Mark Weth for very useful information concerning the construction of the financial wealth data. Hoffmann’s work on this paper is also part of the project The International Allocation of Risk funded by Deutsche Forschungsgemeinschaft in the framework of SFB 475. Responsibility for any remaining errors and shortcomings is entirely our own.     

Price Bubbles in Laboratory Asset Markets with Constant Fundamental Values

We construct asset markets that are similar to those studied by Smith, Suchanek and Williams (Econometrica. 56, 1119–1151) in which bubbles and crashes tended to occur. The main difference between the markets studied here and those studied by Smith et al. is that in the markets studied here, the fundamental value of the asset is constant over the entire life of the asset. In four of the eight sessions reported here, we observe bubbles, which are prices considerably higher than fundamental values. The data suggest that the frequent payment of dividends is a major cause of bubble formation. The property that the fundamental value remains constant over the course of the trading horizon is not sufficient to eliminate the possibility of a bubble.     

Double Bubbles in Assets Markets With Multiple Generations

We construct an asset market in a finite horizon overlapping-generations environment. Subjects are tested for comprehension of their fundamental value exchange environment and then reminded during each of 25 periods of the environment's declining new value. We observe price bubbles forming when new generations enter the market with additional liquidity and bursting as old generations exit the market and withdrawing cash. The entry and exit of traders in the market creates an M shaped double bubble price path over the life of the traded asset. This finding is significant in documenting that bubbles can reoccur within one extended trading horizon and, consistent with previous cross-subject comparisons, shows how fluctuations in market liquidity influence price paths. We also find that trading experience leads to price expectations that incorporate fundamental value.     

Can an overconfident insider coexist with a representativeness heuristic insider?

This paper develops an insider trading model that incorporates the presence of rational, overconfident, and representativeness heuristic insiders. We find that the heuristic insider and overconfident insider trade more aggressively on their information than the rational insider, and that therefore, a higher probability exists for them to earn more profits. Furthermore, both higher heuristic bias of the heuristic insider and greater overconfidence of the overconfident insider lead to less expected profit for the rational insider and less expected loss for the noise trader. Moreover, in an equilibrium, both higher heuristic bias and greater overconfidence of an insider lead to a more efficient and stable market.