The Effects of Subject Pool and Design Experience on Rationality in Experimental Asset Markets

Empirical evidence suggests that prices do not always reflect fundamental values and individual behavior is often inconsistent with rational expectations theory. We report the results of fourteen experimental asset markets designed to examine whether the interactive effect of subject pool and design experience (i.e., previous experience in a market under identical conditions) tempers price bubbles and improves forecasting ability. Our main findings are: 1) price run-ups are modest and dissipate quickly when traders are knowledgeable about financial markets and have participated in a previous market under identical conditions; 2) price bubbles moderate quickly when only a subset of traders are knowledgeable and experienced; 3) the heterogeneity of expectations about price changes is smaller in markets with knowledgeable and experienced traders, even if such traders only represent a subset of the market; and 4) individual forecasts of prices are not consistent with the predictions of the rational expectations model in any market, although absolute forecast errors are smaller for subjects who are knowledgeable of financial markets and for those subjects who have participated in a previous market. In sum, our findings suggest that markets populated by at least a subset of knowledgeable and experienced traders behave rationally, even though average individual behavior can be characterized as irrational.     

Overconfidence and Bubbles in Experimental Asset Markets

This paper investigates the relationship between market overconfidence and occurrence of stock-price bubbles. Sixty participants traded stocks in 10 experimental asset markets. Markets were constructed on the basis of subjects' overconfidence: The most overconfident subjects form high overconfidence markets and the least overconfident subjects low overconfidence markets. Prices in low overconfidence markets tend to track the fundamental asset value more accurately than prices in high overconfidence markets and are significantly lower and less volatile. Additionally, we observe significantly higher bubble measures and trading volume in high overconfidence markets. Two possible explanations for these differences are analyzed: While price expectations are significantly higher in high overconfidence markets, no differences in the average degree of risk aversion were detected.     

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.     

Overreactions,Momentum, Liquidity,and Price Bubbles in Laboratory and Field Asset Markets

Laboratory asset markets provide an experimental setting in which to observe investor behavior. Over more than a decade, numerous studies have found that participants in laboratory experiments frequently drive asset prices far above fundamental value, after which the prices crash. This bubble-and-crash behavior is robust to variations in a number of variables, including liquidity (the amount of cash available relative to the value of the assets being traded), short-selling, certainty or uncertainty of dividend payments, brokerage fees, capital gains taxes, buying on margin, and others.

This paper attempts to model the behavior of asset prices in experimental settings by proposing a "momentum model" of asset price changes. The model assumes that investors follow a combination of two factors when setting prices: fundamental value, and the recent price trend. The predictions of the model, while still far from perfect, are superior to those of a rational expectations model, in which traders consider only fundamental value. In particular, the momentum model predicts that higher levels of liquidity lead to larger price bubbles, a result that is confirmed in the experiments. The similarity between laboratory results and data from field (real-world) markets suggests that the momentum model may be applicable there as well.     

The influence of investment experience on market prices: laboratory evidence

We run laboratory experiments to analyze the impact of prior investment experience on price efficiency in asset markets. Before subjects enter the asset market they gain either no, positive, or negative investment experience in an investment game. To get a comprehensive picture about the role of experience we implement two asset market designs. One is prone to inefficient pricing, exhibiting bubble and crash patterns, while the other exhibits efficient pricing. We find that (i) both, positive and negative, experience gained in the investment game lead to efficient pricing in both market settings. Further, we show that (ii) the experience effect dominates potential effects triggered by positive and negative sentiment generated by the investment game. We conjecture that experiencing changing price paths in the investment game can create a higher sensibility on changing fundamentals (through higher salience) among subjects in the subsequently run asset market.     

Dividend timing and behavior in laboratory asset markets

Summary. This paper investigates the effect of dividend timing on price bubbles and endogenous expectations in twenty-six laboratory asset markets. In ten "A1" markets, a single dividend is paid at the end of the trading horizon. In nine "A2" markets, dividends are paid at the end of each trading period. In seven "A3" markets, some of the dividends are paid at the end of the trading horizon, and the rest are paid on a per-period basis. The results indicate that price bubbles are most likely in A2 markets, less likely in A3 markets, and least likely in A1 markets. Six distinct hypotheses are considered. The data suggest that the concentration of dividend value at a single point in time helps to create common expectations, and thus significantly reduce the incidence of bubbles. Also, the results underscore the difficulty facing econometric tests on field data where fundamental value has to be approximated.     

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.     

Bubble measures in experimental asset markets

We review bubble measures which are commonly used in the experimental asset market literature. It seems sensible to require that measures of mispricing should (i) relate the fundamental value and price, (ii) be monotone in the difference between fundamental value and price, and (iii) be independent of the total number of periods and the absolute level of fundamental value. We show that none of the measures currently used fulfills all these criteria. To facilitate comparability across different experimental settings with different parameterizations we propose two alternative measures which fulfill all evaluation criteria. The measure for mispricing, RAD (relative absolute deviation), is calculated by averaging absolute differences between the (volume-weighted) mean price and the fundamental value across all periods and normalizing it with the absolute value of the average FV of the market. The measure for overvaluation, RD (relative deviation), is calculated analogously, but uses raw difference between (volume-weighted) mean prices and fundamental values. Hence, it provides information on whether the mispricing stems from over- or undervaluation of the asset.     

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.     

BUBBLES,CRASHES, AND ENDOGENOUS UNCERTAINTY IN LINKED ASSET AND PRODUCT MARKETS*

In laboratory asset markets, subjects trade shares of a firm whose profits in a linked product market determine dividends. Treatments vary whether dividend information is revealed once per period or in real time and whether the firm is controlled by a profit‐maximizing robot or human subject. The latter variation induces uncertainty about firm behavior, bridging the gap between laboratory and field markets. Our data replicate well‐known features of laboratory asset markets (e.g., bubbles), suggesting these are robust to a market‐based dividend process. Compared to a sample of previous experiments, both real‐time information revelation and endogenous uncertainty impede the bubble‐mitigating impact of experience.     

Information Markets and the Comovement of Asset Prices

Traditional asset pricing models predict that covariance between prices of different assets should be lower than what we observe in the data. This paper introduces markets for information that generate high price covariance within a rational expectations framework. When information is costly, rational investors only buy information about a subset of the assets. Because information production has high fixed costs, competitive producers charge more for low-demand information than for high-demand information. The low price of high-demand information makes investors want to purchase the same information that others are purchasing. When investors price assets using a common subset of information, news about one asset affects the other assets' prices; asset prices comove. The cross-sectional and time-series properties of comovement are consistent with this explanation.     

FUTURES MARKETS AND BUBBLE FORMATION IN EXPERIMENTAL ASSET MARKETS*

Abstract. We construct asset markets of the type studied in Smith et al. (1988) , in which price bubbles and crashes are widely observed. In addition to a spot market, there are futures markets in operation, one maturing at the beginning of each period of the life of the asset. We find that when futures markets are present, bubbles do not occur in the spot markets. The futures markets seem to reduce the speculation and the decision errors that appear to give rise to price bubbles in experimental asset markets.     

Cognitive bubbles

Smith et al. (Econometrica 56(5):1119, 1988) reported large bubbles and crashes in experimental asset markets, a result that has been replicated many times. Here we test whether the occurrence of bubbles depends on the experimental subjects’ cognitive sophistication. In a two-part experiment, we first run a battery of tests to assess the subjects’ cognitive sophistication and classify them into low or high levels. We then invite them separately to two asset market experiments populated only by subjects with either low or high cognitive sophistication. We observe classic bubble and crash patterns in markets populated by subjects with low levels of cognitive sophistication. Yet, no bubbles or crashes are observed with our sophisticated subjects, indicating that cognitive sophistication of the experimental market participants has a strong impact on price efficiency.     

基于状态空间模型的房地产价格泡沫问题研究

文章首先对房地产价格泡沫进行了理论界定,并对基础价值的特点进行了分析。随后在检验变量之间协整关系的基础上,建立了商品房供给与需求的状态空间模型,基础价值作为一种状态变量被纳入到模型中,从而对上海市房地产价格泡沫问题进行了实证研究。研究结果表明上海市房地产价格泡沫已经出现,并且近四年来平均泡沫程度达到22.5%。     

Can Markets Learn to Avoid Bubbles?

One of the most striking results in experimental economics is the ease with which market bubbles form in a laboratory setting and the difficulty of preventing them. This article re-examines bubble experiments in light of the results of an earlier series of market experiments that show how learning occurs in markets characterized by an asymmetry of information between buyers and sellers, such as found in Akerlof's lemons model and Spence's signaling model. Markets with asymmetric information are incomplete because they lack markets for specific levels of product quality. Such markets either lump all qualities together (lemons) or using external indications of quality to separate them (signaling). Similarly, the markets used in bubble experiments are incomplete in that they are lacking a complete set of forward or futures markets, depriving traders of the information supplied by the prices in those markets. Preliminary experimental results suggest that the addition of a single forward market can sometimes mitigate bubble formation and this article suggests more extensive research in this direction is warranted. Market bubbles outside of the laboratory usually are found in markets in which forward and futures markets are either legally restricted or otherwise limited. Experimentation in markets with asymmetric information also indicates that the ability of subjects to learn how to send and receive signals can be enhanced by changing the way that market information is presented to them. We explore how this result might be used to help asset markets learn to avoid bubbles     

Manipulating market sentiment

We analyze a simple model of an asset market, in which a large rational trader interacts with “noise speculators” who seek short-run speculative gains, and become active following a prolonged episode of mispricing relative to the asset’s fundamental value. The model gives rise to price patterns such as bubble dynamics, positive short-run correlation and vanishing long-run correlation of price deviations from the fundamental value. We argue that this example model sheds light on the question as to whether rational speculators abet or curb price fluctuations.     

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.     

Beauty contest,bounded rationality,and sentiment pricing dynamics

We present a dynamic asset pricing model that incorporates investor sentiment, bounded rationality and higher-order expectations to study how these factors affect asset pricing equilibrium. In the model, we utilize a two-period trading market and investors make decisions based on the heterogeneous expectations principle and the “sparsity-based bounded rational” sentiment. We find that bounded rationality results in mispricing and reduces it in next period. Investor sentiment produces more significant effects than private signals, optimistic investor sentiment increases hedging demand, thus causing prices to soar. Higher-order investors are more rational and attentive to the strategies of other participants rather than private signals. This model also derives the dampening effect of higher-order expectations to price volatility and the heterogeneity expectation depicts inconsistent investor behavior in financial markets. In the model, investors' expectations about future price is distorted by their sentiment and bounded rationality, so they obtain a biased mean from the signal extraction.     

Derivation of Asset Price Equations Through Statistical Inference

We develop a methodology to extract a quantitative model for behavioral effects in markets from empirical data. A set of 24 asset market experiments are utilized to derive an equation of price and its dependence on momentum, fundamental value, excess bid level and liquidity considerations. A difference equation is derived from a statistical analysis of the data. The methods are quite general and can be utilized in conjunction with other behavioral finance effects that influence price dynamics.     

Intrinsic bubbles and asset price volatility

Summary Under what conditions is the price of a bubbly asset more (less) volatile than the asset's market fundamental? The answer depends on agents' attitudes towards risk. If higher current consumption makes agents more (less) risk averse in the future, then the bubbly asset price fluctuates less (more) than the fundamental. This result shows that the interaction between intrinsic bubbles and asset fundamentals critically depends on a feature of the utility function that does not appear in standard models with time-separable utility.Financial support from the Department of Economics at Texas A&M University, the Office for International Coordination at Texas A&M University, and the Deutsche Forschungsgemeinschaft, Sonderforschungsbereich 303 at the University of Bonn, is gratefully acknowledged. The views expressed are those of the authors and do not necessarily represent those of the International Monetary Fund.