and Price Manipulation Incentives (original) (raw)
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Accounting, Organizations and Society, 2004
This study reports the results of fifteen experimental asset markets designed to investigate the effects of forecasts on market prices, traders' abilities to assess asset value, and the link between the two. Across the fifteen markets, the authors investigate alternative forecast-generating processes. In some markets the process produces an unbiased estimate of asset value and in others a biased estimate. The processes generating the biased forecasts, though, are less variable than the process generating the unbiased forecast. The authors find that, in general, periodend asset price reflects private forecasts, regardless of the forecast-generating process. Subsequently, they investigate whether traders' abilities to use forecasts differ across the forecast-generating processes. The authors find that most are able to properly use unbiased forecasts. They refer to them as smart traders. By comparison, a significant proportion is unable to properly use biased forecasts (typically traders' adjustments for bias are insufficient). Linking market outcomes and traders' abilities, the authors find that asset price appears to properly reflect unbiased forecasts as long as the market includes at least two smart informed traders who have sufficient ability to influence market outcomes. To obtain a comparable result in markets with the biased forecast, at least three smart informed traders with sufficient ability to influence market outcomes are necessary.
Forecasting Skills in Experimental Markets: Illusion or Reality?
SSRN Electronic Journal, 2020
Using experimental asset markets, we study the situation of a financial analyst who is trying to infer the fundamental value of an asset by observing the market's history. We find that such capacity requires both standard cognitive skills (IQ) as well as social and emotional skills. However, forecasters with high emotional skills tend to perform worse when market mispricing is high as they tend to give too much emphasis to the noisy signals from market data. By contrast, forecasters with high social skills perform especially well in markets with high levels of mispricing in which their skills could help them detect possible manipulation attempts. Finally, males outperform females in the forecasting task after controlling for a large number of relevant individual characteristics such as risk attitudes, cognitive skills, emotional intelligence, and personality traits.
When better forecasting abilities can be harmful – results from an experimental financial market
Social Science Research Network, 2005
The question of how useful information in a financial market is has been discussed for decades and is still unresolved. In this paper we challenge the widely held belief that success and failure in the stock market can largely be attributed to the information underlying the trading decisions. We present a dynamic multi-period experimental financial market with asymmetrically informed traders whose information is based on future dividends. While the best informed traders can outperform the market, we find that information is not always useful, as average informed traders have significantly lower net returns than the worst informed.
Documentos de trabajo (FEDEA), 2008
We study with the help of a laboratory experiment the conditions under which an uninformed manipulator -a robot trader that unconditionally buys several shares of a common value asset in the beginning of a trading period and unwinds this position later on -is able to induce higher asset prices. We find that the average contract price is significantly higher in the presence of the manipulator if, and only if, the asset takes the lowest possible value and insiders have perfect information about the true value of the asset. It is also evidenced that the robot trader makes trading gains; i.e., independently on whether the informed traders have perfect or partial information, it earns always more than the average trader. Finally, not only uninformed subjects suffer from the presence of the robot trader, but also some of the imperfectly informed insiders have lower payoffs once the robot trader is added as a market participant.
Can better forecasting abilities be harmful? Evidence from experimental asset markets
The question of how useful information in financial markets is has been discussed for decades and is still unresolved. In this paper we challenge the widely held belief that success and failure in the stock market can largely be attributed to the information underlying the trading decisions. We present a dynamic multi-period experimental financial market with asymmetrically informed traders whose information is based on future dividends. While the best informed traders can outperform the market, we find that information is not always useful, as average informed traders have significantly lower returns than the worst informed. JEL-classification: C91; D82; D83, G10 Keywords: Value of information, asymmetric information, experimental economics, information structure # Without useful suggestions from and discussions with several colleagues this paper would not have made it to this final version. We would especially like to thank Michael Hanke, Klaus Schredelseker, Matthias Sutter, and Florian Hauser for their helpful contributions. Financial support from the University of Innsbruck is gratefully acknowledged
Journal of Economic Dynamics and Control, 2018
In this study, we investigate (a) whether eliciting future price forecasts influences market outcomes and (b) whether differences in the way in which subjects are incentivized to submit "accurate" price forecasts influence market outcomes as well as the forecasts in an experimental asset market. We consider four treatments: one without forecast elicitation and three with forecast elicitation. In two of the treatments with forecast elicitation, subjects are paid based on their performance in both forecasting and trading, while in the other treatment with forecast elicitations, they are paid based on only one of those factors, which is chosen randomly at the end of the experiment. We found no significant effect of forecast elicitation on market outcomes in the latter case. Thus, to avoid influencing the behavior of subjects and market outcomes by eliciting price forecasts, paying subjects based on either forecasting or trading performance chosen randomly at the end of the experiment is better than paying them based on both. In addition, we consider forecast-only experiments: one in which subjects are rewarded based on the number of accurate forecasts and the other in which they are rewarded based on a quadratic scoring rule. We found no significant difference in terms of forecasting performance between the two.
A multi-agent system for analyzing the effect of information on prediction markets
International Journal of Intelligent Systems, 2011
Prediction markets have been shown to be a useful tool for forecasting the outcome of future events by aggregating public opinion about the event's outcome. In this paper, we investigate an important aspect of prediction markets—the effect of different information-related parameters on the behavior of the traders in the market. We have developed a multi-agent based system that incorporates different information-related aspects including the arrival rate of information, the reliability of information, the penetration or accessibility of information among the different traders, and the perception or impact of information by the traders. We have performed extensive simulations of our agent-based prediction market for analyzing the effect of information-related parameters on the traders' behaviors expressed through their trading prices, and compared our agents' strategies with another agent-based pricing strategy used in prediction markets called the zero intelligence strategy. Our results show that information-related parameters have a significant impact on traders' beliefs about event outcomes, and, frequent, reliable information about events improves the utilities that the traders receive. Overall, our work provides a better understanding of the effect of information on the operation of prediction markets and on the strategies used by the traders in the market. © 2011 Wiley Periodicals, Inc.
Information aggregation in experimental asset markets in the presence of a manipulator
Documentos de trabajo (FEDEA), 2008
We study with the help of a laboratory experiment the conditions under which an uninformed manipulator - a robot trader that unconditionally buys several shares of a common value asset in the beginning of a trading period and unwinds this position later on - is able to induce higher asset prices. We find that the average contract price is significantly higher in the presence of the manipulator if, and only if, the asset takes the lowest possible value and insiders have perfect information about the true value of the asset. It is also evidenced that the robot trader makes trading gains; i.e., independently on whether the informed traders have perfect or partial information, it earns always more than the average trader. Finally, not only uninformed subjects suffer from the presence of the robot trader, but also some of the imperfectly informed insiders have lower payoffs once the robot trader is added as a market participant.
A methodological note on eliciting price forecasts in asset market experiments
2016
We investigate (a) whether eliciting future price forecasts influences market outcomes, and (b) whether differences in the way subjects are incentivized to submit ''accurate'' price forecasts influence the market outcomes as well as the forecasts submitted by subjects in an experimental asset market. We consider three treatments: one without forecast elicitation (NF) and two with forecast elicitations. In one of the latter treatments, subjects are paid based on both their performance of forecasting and trading (Bonus), while in the other, they are paid based only on one of the two that is chosen randomly at the end of the experiment (Unique). While we found no statistical differences in terms of mispricing, trading volumes, and trading behavior between NF and Unique treatments, there were some statistically significant differences between NF and Bonus treatments. Thus, if the aim is to avoid influencing the behavior of subjects and the market outcomes by eliciting pr...