An empirical evaluation of the overconfidence hypothesis

Recently, several behavioral finance models based on the overconfidence hypothesis have been proposed to explain anomalous findings, including a short-term continuation (momentum) and a long-term reversal in stock returns. We characterize the overconfidence hypothesis by the following four testable implications: First, if investors are overconfident, they overreact to private information and underreact to public information. Second, market gains make overconfident investors trade more aggressively in subsequent periods. Third, excessive trading of overconfident investors in securities markets contributes to the observed excessive volatility. Fourth, overconfident investors underestimate risk and trade more in riskier securities. To document the presence of overconfidence in financial markets, we empirically evaluate these four hypotheses using aggregate data. Overall, we find empirical evidence in support of the four hypotheses.     

信息不对称、过度自信与股价变动

信息传导的非同步和投资者情绪变化是股票市场的两个典型特征,前者会引发投资者之间出现信息不对称问题,后者主要体现为投资者过度自信,两者共同作用影响股票价格变动。本文将信息不对称和投资者过度自信情绪置于同一个分析框架,建立两阶段动态序贯定价理论模型研究现实市场上信息传导过程中股价变动的内在机制。结果表明:(1)面临新信息的进入,投资者对股票收益预期的调整与均衡价格之间具有正相关关系;(2)面临有利消息时,过度自信投资者比例越大,股票的均衡价格越高,投资收益将越低;面临不利消息时则相反;(3)随着过度自信投资者比例以及过度自信程度升高,市场风险溢价将下降;(4)投资者群体在信息传导过程中出现分化,对股价变动形成异质信念,未获取信息和获取信息但未出现过度自信的投资者认为股价被高估,获取信息且出现过度自信的投资者认为价格被低估,促使更多的交易,引发市场成交量和股价变动;(5)过度自信投资者比例与过度自信程度提高均会对市场效率产生正向影响,而对市场深度具有负向效应。最后,基于理论结果对非对称性和持续性等典型的市场波动性特征进行解释。     

Learning to be overconfident

We develop a multiperiod market model describing both the processby which traders learn about their ability and how a bias inthis learning can create overconfident traders. A trader inour model initially does not know his own ability. He infersthis ability from his successes and failures. In assessing hisability the trader takes too much credit for his successes.This leads him to become overconfident. A trader's expectedlevel of overconfidence increases in the early stages of hiscareer. Then, with more experience, he comes to better recognizehis own ability. The patterns in trading volume, expected profits,price volatility, and expected prices resulting from this endogenousoverconfidence are analyzed.     

Who is the more overconfident trader? Individual vs. institutional investors

Guided by the Gervais and Odean (2001) overconfident trading hypothesis, we comprehensively investigate the trading behavior of individual vs. institutional investors in Taiwan in an attempt to identify who is the more overconfident trader. Conditional on the various states of the market, on market volatility, and on the risk level of the securities they trade, we find that both individual and institutional investors trade more aggressively following market gains in bull markets, in up-market states, in up-momentum market states, and in low-volatility market states and that only individual investors trade more in riskier securities following market gains. More importantly, we find that individual investors trade more aggressively following market gains in the three conditional states of the market and in high-volatility market states than institutional investors. Also, individual investors trade more in relatively riskier securities following gains than institutional investors. These findings provide evidence that individual investors are more overconfident traders than institutional investors.     

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.     

Learning from others,reacting, and market quality

Traders pay attention to one another but are unable to perfectly deduce each others’ beliefs from transactions alone. This explains why markets are hard to beat and also why trading occurs at all. Even when traders react rationally to the actions of others, they cannot arrive easily at a common posterior assessment of value. We model a realistic market composed of traders who combine their own private information with rational learning about the information possessed by others. We compare phenomena in this market with an otherwise identical market populated by traders who receive the same private information but ignore other traders. Using simulation to engender greater realism, we find that learning usually reduces volatility, increases the accuracy of the market price as a forecast of value, reduces trading volume, and decreases the prevalence of bubbles. However, for some combinations of market conditions, learning can have the opposite effect. The marginal influences of eight different market conditions, ranging from information heterogeneity through resource diversity, are estimated. Prices, volatility, volume, and bubbles exhibit subtle and complex responses to market conditions.     

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.     

A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets

We model a market populated by two groups of boundedly rational agents: "newswatchers" and "momentum traders." Each newswatcher observes some private information, but fails to extract other newswatchers' information from prices. If information diffuses gradually across the population, prices underreact in the short run. The underreaction means that the momentum traders can profit by trend-chasing. However, if they can only implement simple (i.e., univariate) strategies, their attempts at arbitrage must inevitably lead to overreaction at long horizons. In addition to providing a unified account of under- and overreactions, the model generates several other distinctive implications.     

Overconfident individual day traders: Evidence from the Taiwan futures market

A specific day-trading policy in Taiwan futures market allows an investigation of the performance of day traders. Since October 2007, investors who characterize themselves as “day traders” by closing their day-trade positions on the same day enjoy a 50% reduction in the initial margin. Because we can identify day traders ex ante, we have a laboratory to explore trading behavior without the contamination of potential behavioral biases. Our results show that the 3470 individual day traders in the sample incur on average a significant loss of 61,500 (26,700) New Taiwan dollars after (before) transaction costs over October 2007–September 2008. This implies that day traders are not only overconfident about the accuracy of their information but also biased in their interpretations of information. We also find that excessive trading is hazardous only to the overconfident losers, but not to the winners. Last, we provide evidence that more experienced individual investors exhibit more aggressive day trading behavior, although they do not learn their types or gain superior trading skills that could mitigate their losses.     

Earnings Metrics,Information Processing,and Price Efficiency in Laboratory Markets

An enduring issue in financial reporting is whether and how salient summary measures of firm performance (“earnings metrics”) affect market price efficiency. In laboratory markets, we test the effects of salient earnings metrics, which vary in how they combine persistent and transitory elements, on investor information search, beliefs about value, offers to trade, and market price efficiency. We find that including transitory elements in salient earnings metrics causes traders to search unnecessarily for further information about these elements and to overestimate their effect on fundamental value relative to a rational benchmark. In contrast, separately displaying persistent elements in earnings increases the accuracy of traders’ value estimates. Prices generally reflect traders’ beliefs about value, and prices are most efficient when transitory elements are excluded from earnings metrics entirely. Our study contributes to research on salience effects in financial reporting by showing that including transitory elements in salient earnings metrics causes inefficient information search and biased beliefs about value that can aggregate to affect market prices. We also contribute to research in experimental markets by showing that redundant disclosure is not always beneficial; redundant disclosure of transitory earnings elements, in particular, appears to have negative consequences for investor behavior and market efficiency.     

Financial Markets Where Traders Neglect the Informational Content of Prices

We model a financial market where some traders of a risky asset do not fully appreciate what prices convey about others' private information. Markets comprising solely such “cursed” traders generate more trade than those comprising solely rationals. Because rationals arbitrage away distortions caused by cursed traders, mixed markets can generate even more trade. Per‐trader volume in cursed markets increases with market size; volume may instead disappear when traders infer others' information from prices, even when they dismiss it as noisier than their own. Making private information public raises rational and “dismissive” volume, but reduces cursed volume given moderate noninformational trading motives.     

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.     

Does news travel slowly before a market crash? The role of margin traders

We investigate how investor overconfidence and attention affect market efficiency around the 2015 Chinese stock market crash. We find that the price delay before the crash is about twice the price delay after the crash. Investors become more sensitive to market movements after the crash. Price delays are larger on market down-days than on up-days before the crash, but the differences are insignificant between up- and down-days after the crash, indicating that negative information travels slowly only when investors are overconfident. Margin traders follow market trends and intensify the pyramiding and de-pyramiding effects caused by market sentiment change.     

Trade Disclosure,Information Learning and Securities Market Performance

In this paper we examine the effect of information disclosure on securities market performance when liquidity traders are able to acquire information about inside trading. We show that the bid-ask spread increases with the liquidity trader's learning efficiency, which is greater when trade information is disclosed. The bid-ask spread is always higher when trade information is not disclosed. However, the discrepancy between the bid-ask spreads with and without information disclosure narrows when the learning efficiency increases. We also show that the gains of the informed traders in a market without trade information disclosure are reduced in the presence of the liquidity trader's learning. Nevertheless, liquidity traders do not necessarily benefit from increased transparency. In particular, liquidity traders may face higher trading costs.     

Investor Sentiment,Trading Behavior and Informational Efficiency in Index Futures Markets

This paper shows that traders in index futures markets are positive feedback traders—they buy when prices increase and sell when prices decline. Positive feedback trading appears to be more active in periods of high investor sentiment. This finding is consistent with the notion that feedback trading is driven by expectations of noise traders. Consistent with the noise trading hypothesis, order flow in index futures markets is less informative when investors are optimistic. Transitory volatility measured at high frequencies also appears to decline in periods of bullish sentiment, suggesting that sentiment‐driven trading increases market liquidity.     

Technical Analysis as a Rational Tool of Decision Making for Professional Traders

The psychological background of technical analysis usage is investigated to further explain the popularity and common usage of technical analysis as an investment decision tool. Attitudes toward technical analysis of professional futures market traders and neophyte investors, represented by finance students, were examined. Technical analysis is one of the most popular methods supporting investment decisions and it is much more popular among future market traders than among neophyte investors. The concept of processing information was used to explain this phenomenon. Neophyte investors are more experiential and intuition-driven while using technical analysis models, while futures market traders are more rationally driven. Technical analysis methods help professional traders on futures markets, which are less transparent than regulated stock markets, to process information; those methods are perceived by them as rational, cognitive tools supporting their decision making.     

A Comparison of Centralized and Fragmented Markets with Costly Search

How does quotation transparency affect financial market performance? Biais's irrelevance proposition in 1993 shows that centralized markets yield the same expected bid–ask spreads as fragmented markets, other things equal. However, de Frutos and Manzano demonstrated in 2002 that expected spreads in fragmented markets are smaller and market participants prefer to trade in fragmented markets. This paper introduces liquidity traders' costs of searching for a better quote into the Biais model and derives opposite conclusions to these previous studies: expected spreads in centralized markets are smaller and liquidity traders prefer centralized markets, while market makers prefer fragmented markets.     

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.     

Market making with minimum resting times

We show how the supply of liquidity in order-driven markets is affected if limit orders (LOs) are forced to rest in the limit order book for a minimum resting time (MRT) before they can be cancelled. The bid-ask spread increases as the MRT increases because market makers (MMs) increase the depth of their LOs to protect them from being picked off by other traders. We also show that the expected profits of the MMs increase when the MRT increases. The intuition is as follows. As the MRT increases, there are two opposing forces at work. One, the longer the MRT, the more likely the LOs are to be filled and, on average, shares are sold at a loss. Two, because the depth of the posted LOs increases, the probability that the LO is picked off by other traders before the end of the MRT decreases. The net effect is that a longer MRT leads to a higher expected profit. We also show that the depth of LOs increases when the volatility of the price of the asset increases. Also, the depth of LOs increases when the arrival rate of market orders increases because it is less likely that LOs will be picked off by the end of the MRT. Finally, our model also makes predictions about the overall liquidity of the market. We show that MMs choose to supply the minimum amount of shares per LO allowed by the exchange because expected profits are maximised when liquidity provided is lowest.     

Market Efficiency, Bounded Rationality, and Supplemental Business Reporting Disclosures

The AICPA Special Committee on Financial Reporting has urged disclosure of relevant forward-looking information on risks and opportunities to supplement conventional financial statements. We conduct a laboratory market experiment to assess the effects of such disclosures on capital allocation decisions. We develop two sets of competing hypotheses regarding how capital markets react to supplemental disclosures. One set is based on the assumption of semi-strong market efficiency, while the other posits that the bounded rationality of individual traders leads to inefficient market prices. We find that explicit disclosure of management's best estimate of an uncertain quantity improves market efficiency, even though this disclosure is redundant with information in financial statements. Second, we find disclosure of an upper bound of management's estimate has the potential to bias security prices upward, while informationally equivalent disclosure of both upper and lower bounds removes this bias. These results suggest that experimental market reactions to these supplemental disclosures are inconsistent with market efficiency. Supplemental analyses of individuals' price predictions and trading behavior support our conclusion that inefficiencies are at least partially attributable to individual information processing biases.