Rational Herding Research Articles

On Crowdfunding Success: Firm and Owner Attributes and Social Networking

This study investigates the role of platform-mandated disclosure, firm and owner attributes and social networking activity on the success of crowdfunding campaigns. It is found that more stringent platform disclosure requirements and risk warnings are not associated with success of crowdfunding campaigns. However, owner experience and firm-specific financial statement information are correlated with crowdfunding success. Moreover, social networking, at least as measured by the frequency of social media contacts, also plays a role. Those two findings combined suggest that social media encourage crowdinvestors’ rational herding and make crowdfunding investment decisions that are informed by both the wisdom of the crowd and the quality of the opportunity.

Why is Unemployment Duration a Sorting Criterion in Hiring?

Recent evidence from large-scale field experiments has shown that employers use job candidates' unemployment duration as a sorting criterion. In the present study, we investigate the mechanisms underlying this pattern. To this end, we conduct a lab experiment in which participants make hiring decisions concerning fictitious job candidates with diverging unemployment durations. In addition, these participants rate the job candidates on statements central to four theoretical mechanisms often related to the scarring effect of unemployment: general signalling theory, (perceived) skill loss, queuing theory, and rational herding. We use the resulting data to estimate a multiple mediation model, in which the effect of the duration of unemployment on hiring intentions is mediated by the four theories. The lower hiring chances of the long-term unemployed turn out to be dominantly driven by the perception of longer unemployment spells as a signal of lower motivation. Recent evidence from large-scale field experiments has shown that employers use job candidates' unemployment duration as a sorting criterion. In the present study, we investigate the mechanisms underlying this pattern. To this end, we conduct a lab experiment in which participants make hiring decisions concerning fictitious job candidates with diverging unemployment durations. In addition, these participants rate the job candidates on statements central to four theoretical mechanisms often related to the scarring effect of unemployment: general signalling theory, (perceived) skill loss, queuing theory, and rational herding. We use the resulting data to estimate a multiple mediation model, in which the effect of the duration of unemployment on hiring intentions is mediated by the four theories. The lower hiring chances of the long-term unemployed turn out to be dominantly driven by the perception of longer unemployment spells as a signal of lower motivation.

Word-of-Mouth, Observational Learning, and Product Adoption: Evidence from an Anime Platform

We quantify the effects of word-of-mouth and observational learning on consumers' product adoptions. Understanding whether these two forces provide different and unique information or whether one is redundant in the presence of the other is crucial for companies' information provision strategies. We differentiate between the effects of word-of-mouth and observational learning from friends (personal network) and the effects of word-of-mouth and observational learning from the whole community (``community network). The relative importance of word-of-mouth and observational learning at each network level provides guidance for companies regarding their platform design. Our unique data come from an online anime platform containing individual-level data on users' networks, product adoptions, and ratings of animes. Our results reveal two segments of users: a small segment of Enthusiasts who tend to watch more animes and to adopt them earlier, and a larger segment of Regular Watchers who tend to watch fewer animes and to adopt them later. For both segments of users, word-of-mouth from the community network is the largest driver of users' product adoptions followed by observational learning from the community network. Thus our results show that word-of-mouth and observational learning provide unique and different information that individuals use in their product adoption decisions and that the community network is the primary source of information. Lastly, using our results, we test for image utility, for observational learning creating product awareness versus transferring unobserved quality information, and for rational herding.

Rational Herding toward the Poor: Evidence from Location Decisions of Microfinance Institutions within Pakistan

Analyzing the geographical location of almost all the microfinance institutions (MFIs) within Pakistan, this paper gives further evidence that microfinance activities do not reach the poorest rural areas. Especially, we explore how this result is driven by the uncertainty faced by MFIs in their location decision i.e., they can hardly predict accurately whether or not they will perform financially. Furthermore, we find that MFIs are spatially clustered and identify three main reasons for this: common attraction factors i.e., the characteristics of one area fits to the preferences of all MFIs so that they are all located in the same areas; payoff externalities to be collocated; and herd behavior, i.e., MFIs follow one another. Most importantly, we find that a significant part of this herding process is rational, i.e., early locations of MFIs convey information used by later ones such that it reverses or neutralizes the negative impact of uncertainty resulting then in more locations in needier areas. Since it allows them to be located in poorer areas, MFIs improve the achievement of their social goal. This latter result is rather good news for those who reckon that a better access to financial services enhances economic growth and fosters poverty alleviation. Indeed, rational herding constitutes an endogenous moderator effect to the big issue that financial services penetration is too weak in the poorest rural areas.

IN SEARCH OF CASH‐FLOW PRICING

AbstractThere are varying views on the relative importance of cash flow versus earnings in the pricing of stocks. In this article, we identify which financial metric—cash flow or earnings—is more often used by investors in equity valuation and then investigate why investors focus on one more than the other. Our prior is that the practice of deviating from cash‐flow pricing, if it exists, can be explained by either rational herding or information cascades. We find that although stock prices are, on average, affected by short‐term earnings, cash‐flow pricing is used primarily to price what we classify as “negative” stocks—stocks that are generally characterized as illiquid, mispriced, or having a shorter trading history, negative earnings, or negative market performance. We find evidence consistent with the rational argument of information cascades. For stocks under close public scrutiny, investors tend to follow the decisions of others and feel compelled to conform to the majority even though their private information suggests otherwise. In the end, the choice to value stocks with either earnings or cash flow is still a rational one.

Efficiency or bounded rationality? Drivers of firm diversification strategies in Vietnam

Considering the case of diversified firms within a developing/transition country such as Vietnam, this paper investigates diversification relatedness while taking into account both firm- and industry-specific components. The high volatility of the dynamics of diversification observed in Vietnam suggests the hypothesis that firms decide to enter into new industries following a trial and error process, initiated by boundedly rational herding behaviors, i.e., firms follow the most commonly observed business combinations. Using a survivor-based (SB) measure of relatedness, we test the hypothesis of boundedly rational behavior. We find that both the probability of exit and the different performance measures (Return on sales and Total factor productivity) are not or are negatively correlated with SB-related diversification. This is in contrast to what has been observed in developed countries. However, using the SIC distance approach, we obtain the expected positive relationship between performance and relatedness in diversified firms. The conflicting result between these two relatedness indices therefore suggests there has been a trend in follow-up among inexperienced firms that imitate the direction and intensity of the diversification of dominating players within the industry (herd behavior). However, diversified firms gain experience over time and choose more efficient business combinations in subsequent entries. When we use the classical SIC-based approach, we find that greater diversification raises profitability, but only to an optimum relatedness point, beyond which the positive effect fades away. To control for the endogeneity of diversification relatedness and the serial correlation in error terms, we adopt an instrumental-variable two-stage least-squares estimation approach (IV-2SLS) with GMM treatment.

Strategic Coordination in Forecasting. An Experimental Study

Reputational herding has been considered as a driving force behind economic and financial forecasts clustered around consensus values. Strategic coordination can consequently explain poor performances of prediction markets as resulting from the distinct incentives that forecasters face. While this notion has been considered theoretically and empirically, the underlying behavioral working mechanisms have not yet been described. We thus put forth an exploratory experiment on the emergence and robustness of coordination in a forecasting setting implementing contradictory incentives for accurate forecasts and coordination. Forecasts are shown to be inaccurate and biased toward current values. This in turn has subjects aiming at coordination benefits. Predominantly, coordination is achieved through the risk-dominant equilibrium as the game proceeds. Once established, coordination is fairly stable and adds to overall welfare. Our results support the assumption of rational herding as a driving force for predictions of poor accuracy that are systematically biased towards focal points.

Estimating a Structural Model of Herd Behavior in Financial Markets

We develop a new methodology to estimate herd behavior in financial markets. We build a model of informational herding that can be estimated with financial transaction data. In the model, rational herding arises because of information-event uncertainty. We estimate the model using data on a NYSE stock (Ashland Inc.) during 1995. Herding occurs often and is particularly pervasive on some days. On average, the proportion of herd buyers is 2 percent; that of herd sellers is 4 percent. Herding also causes important informational inefficiencies in the market, amounting, on average, to 4 percent of the asset's expected value. (JEL C58, D82, D83, G12, G14)

Herding and the shifting determinants of exchange rate regime choice

It is difficult to pin down the factors that determine states’ choice of exchange rate regime because those very factors present a moving target. Many scholars have taken on the same question: what are the determinants of exchange rate regime choice? But as a group they have been unable to identify a stable answer. The reason for this is that the factors that best predict exchange rate regime vary dramatically across time. An explanation for this variation is offered: rational herding, or information cascades, can explain why one factor becomes prominent for a period of time then suddenly drops off and is replaced by a better predictor.

Social Learning Among Rational Analysts

This paper empirically investigates learning among financial forecasters. I test for informational cascades or rational herd behavior among financial analysts. I conduct a set of nonparametric tests and show that analysts not only learn but also believe that their predecessors learn from each other. I also test a structural parametric model of social learning among financial analysts. This comes around the problem of common information in influencing similar forecasts among analysts. Here, too, I find no evidence that analysts make independent forecasts.

Rational Herding in Microloan Markets

Microloan markets allow individual borrowers to raise funding from multiple individual lenders. We use a unique panel data set that tracks the funding dynamics of borrower listings on Prosper.com, the largest microloan market in the United States. We find evidence of rational herding among lenders. Well-funded borrower listings tend to attract more funding after we control for unobserved listing heterogeneity and payoff externalities. Moreover, instead of passively mimicking their peers (irrational herding), lenders engage in active observational learning (rational herding); they infer the creditworthiness of borrowers by observing peer lending decisions and use publicly observable borrower characteristics to moderate their inferences. Counterintuitively, obvious defects (e.g., poor credit grades) amplify a listing's herding momentum, as lenders infer superior creditworthiness to justify the herd. Similarly, favorable borrower characteristics (e.g., friend endorsements) weaken the herding effect, as lenders attribute herding to these observable merits. Follow-up analysis shows that rational herding beats irrational herding in predicting loan performance. This paper was accepted by Pradeep Chintagunta, marketing.

Management Insights

Management Insights

Existence of Capital Market Equilibrium in the Presence of Herding and Feedback Trading

This paper attempts to establish the existence of equilibrium, in an asset market inhabited by two representative investors with different risk aversions. In order to capture heterogeneity in information and wealth, the paper segments the investor population into two: (i) Individual investors and (ii) Institutional investors. Based on prior literature, the present study posits that Institutional investors demonstrate rational intentional herding and positive feedback trading (buy when the markets rise and sell when it falls) and individual investors demonstrate negative feedback trading (vice versa). In other words, when the markets are (monotonically) increasing, institutional investors, expecting the trend to continue would buy more, thus demonstrating decreasing absolute risk aversion. Similarly, when the market is (monotonically) decreasing he will try to stem his loss as soon as possible, demonstrating increasing absolute risk aversion. Such an investment behavior is captured in a power utility function. Further, negative feedback trading by individual investors implies that when market is (monotonically) increasing individual investors, expecting the trend to reverse, would sell. Thus demonstrating increasing absolute risk aversion. And when the markets are (monotonically) decreasing, they would hold on to their investments expecting better times to come, thus depicting decreasing absolute risk aversion. Such investment behavior is captured by a quadratic utility function. Given their wealth and investment behavior, the two investor groups would trade with each other such that the market clears. To the best of our knowledge this is the first paper that proposes a asset pricing model that not only allows for behavioural biases but also for heterogeneous agents who are affected differently by these biases. This paper establishes the bounds for the absolute risk aversion function and the shadow rate of interest at which the two investor groups will lend money to each other to enable trading and market clearing. For reasonable endowments and presumed behavioural biases as implied by the chosen utility function, a numerical example at the end of this paper shows that the market clearing interest rate (at which the investors would lend to and borrow from each other) occurs between 15.5% and 28.05%.

Estimating a Structural Model of Herd Behavior in Financial Markets

We develop a new methodology to estimate the importance of herd behavior in financial markets: we build a structural model of informational herding that can be estimated with financial transaction data. In the model, rational herding arises because of information-event uncertainty. We estimate the model using data on a NYSE stock (Ashland Inc.) during 1995. Herding often arises and is particularly pervasive on some days. The proportion of herd buyers (sellers) is 2 percent (4 percent) and is greater than 10 percent in 7 percent (11 percent) of information-event days. Herding causes important informational inefficiencies, amounting, on average, to 4 percent of the expected asset value.

Herding and Contrarian Behavior in Financial Markets

Rational herd behavior and informationally efficient security prices have long been considered to be mutually exclusive but for exceptional cases. In this paper we describe the conditions on the underlying information structure that are necessary and sufficient for informational herding and contrarianism. In a standard sequential security trading model, subject to sufficient noise trading, people herd if and only if, loosely, their information is sufficiently dispersed so that they consider extreme outcomes more likely than moderate ones. Likewise, people act as contrarians if and only if their information leads them to concentrate on middle values. Both herding and contrarianism generate more volatile prices, and they lower liquidity. They are also resilient phenomena, although by themselves herding trades are self-enforcing whereas contrarian trades are self-defeating. We complete the characterization by providing conditions for the absence of herding and contrarianism.

Ambiguity aversion and rational herd behaviour

This article reviews the literature on herd behaviour in financial markets in the context of the sequential trading model and points out the importance of incorporating ambiguity into the framework. Although Ford et al. (2005) have applied the Choquet-expected-utility theory to analyse the relationship between ambiguity and herd behaviour, their model does not allow for the separation between ambiguity and ambiguity aversion, therefore how ambiguity and ambiguity aversion affect herd behaviour cannot be analysed by comparative statistics. This article adopts the smooth model suggested by Klibanoff et al. (2005), and applies Gollier's (2006) value function to describe decision makers’ welfare under ambiguity. Using very general assumptions, we prove that if the value functions of market makers and traders are homogeneous, herd behaviour will never happen even if ambiguity exists; if some types of traders have different attitudes towards ambiguity from market makers, then herd behaviour will happen with a p...

Estimating a Structural Model of Herd Behavior in Financial Markets

We develop a new methodology to estimate the importance of herd behavior in financial markets: we build a structural model of informational herding that can be estimated with financial transaction data. In the model, rational herding arises because of information-event uncertainty. We estimate the model using data on a NYSE stock (Ashland Inc.) during 1995. Herding often arises and is particularly pervasive on some days. The proportion of herd buyers (sellers) is 2 percent (4 percent) and is greater than 10 percent in 7 percent (11 percent) of information-event days. Herding causes important informational inefficiencies, amounting, on average, to 4 percent of the expected asset value.

Estimating a Structural Model of Herd Behavior in Financial Markets

We develop a new methodology to estimate the importance of herd behavior in financial markets: we build a structural model of informational herding that can be estimated with financial transaction data. In the model, rational herding arises because of information-event uncertainty. We estimate the model using data on a NYSE stock (Ashland Inc.) during 1995. Herding often arises and is particularly pervasive on some days. The proportion of herd buyers (sellers) is 2 percent (4 percent) and is greater than 10 percent in 7 percent (11 percent) of information-event days. Herding causes important informational inefficiencies, amounting, on average, to 4 percent of the expected asset value.

Rational Bias and Herding in Analysts' Recommendations

Rational Bias and Herding in Analysts' Recommendations

Portfolio choice when relative income matters

This paper derives conditions under which concerns about relative income produce rational herding—the shift of individuals’ portfolios into the same direction as others’. To endure the generality of results, the model makes parsimonious behavioral assumptions and no assumption about the functional form of utility. The two most critical conditions are substitutability between one's own income and relative income and diminishing marginal utility of relative income. The keeping-up-with-the-Joneses (KUJ) motive unambiguously contributes to rational herding. When relative income is viewed as a measure of status, however, the KUJ motive is neither a necessary nor a sufficient condition.