Abstract We operationalize Stein’s (2009) overcrowding concept in the context of investor response to daily stock return shocks and examine its underlying behavioral motivation. We define chasing at the overshooting point as evidence of overcrowding. Using trading data by investor type from Korea, we find that while institutional investors display informed trading, they fail to recognize the predictable

Abstract In this paper, we use a Quantile Structural Vector Autoregressive (QSVAR) model, estimated over the quarterly period of 1975:Q3 to 2017:Q3, to analyze whether the impact of monetary policy shocks on growth rate of real house price in the United States is contingent on the initial state of housing market sentiment. We find that contractionary monetary policy reduces growth rate of real house

Abstract A company’s operational uncertainty resulting from economic activity could be measured by its contingent liabilities. When the contingent liabilities are forecasted by the analysts, the dispersed analysts’ forecasts might constitute another source of uncertainty. In this study, the Uncertainty (contingent liabilities) of Uncertainty (dispersed analysts’ forecasts) is measured by the UOU indicator

Abstract A company’s operational uncertainty resulting from economic activity could be measured by its contingent liabilities. When the contingent liabilities are forecasted by the analysts, the dispersed analysts’ forecasts might constitute another source of uncertainty. In this study, the Uncertainty (contingent liabilities) of Uncertainty (dispersed analysts’ forecasts) is measured by the UOU indicator

Abstract The authors examine whether acquiring companies strategically time their quarterly earnings and merger and acquisition announcements. Acquiring companies have the ability and incentive to alter the sequence of these 2 types of announcements to optimize the market’s perception of the firm. The authors show that acquiring companies are more likely to announce earnings before mergers and acquisitions

Abstract We analyze the exchange rate forecasting performance under the assumption of selective attention. Although currency markets react to a variety of different information, we hypothesize that market participants process only a limited amount of information. Our analysis includes more than 100,000 news articles relevant to the six most-traded foreign exchange currency pairs for the period of 1979–2016

Abstract In contrast to the conventional view that analysts forecast optimistically, we provide evidence of the Negativity Bias. Analysts show negative forecast bias associated with their relative local income growth, whether the growth is positive or negative. The bias is stronger for negative growth than for positive growth. The negative bias also directly affects the bias of the next analysts of

Abstract Researchers have documented that individuals have a strong penchant for round numbers in a variety of settings, such as trading in financial markets. Beginning as early as the 1930s, empirical research has shown that security prices tend to cluster on round increments. This anomalous finding has persisted over time and in a wide range of different types of securities markets. We examine whether

Abstract This article examines whether incorporating investors’ uncertainty, as captured by the conditional volatility of sentiment, can help forecasting volatility of stock markets. In this regard, using the Markov-switching multifractal (MSM) model, we find that investors’ uncertainty can substantially increase the accuracy of the forecasts of stock market volatility according to the forecast encompassing

Abstract This paper uses the cross-sectional absolute deviation (CSAD) in static and time-varying versions to examine herding in the cryptocurrency market from April 2013 to November 2019. Results from the static model confirm the evidence of an anti-herding behavior over the considered period. However, the time-varying analysis suggests the presence of herding behavior around the end of 2013 and persists

Abstract This article uses public perceptions to forecast short-term fluctuations in asset prices. Based on four billion tweets scraped between 2009 and 2019, I perform textual analysis to construct daily sentiment indices. The sentiment indices allow us to forecast stock volatility jumps as well as expected jump levels. The implications of forecasting volatility jumps are substantive. First, volatility

Abstract This study introduces a comprehensive Google search volume based Bitcoin Sentiment Index (BSI) and investigates its symmetric and asymmetric association with Bitcoin's returns, volume, and volatility, and with United States Dollar (USD) exchange rates. Our results indicate a positive association of BSI with Bitcoin's returns and volume, but a negative relationship with its return volatility

Abstract Sentiment indicators have long been closely monitored by economic forecasters, notably to predict short-term moves in consumption and investment. Recently, housing sentiment indices have been developed to forecast housing market developments. Sentiment indices partly reflect economic determinants, but also more subjective factors, thereby adding information, particularly in periods of uncertainty

Abstract XBRL (eXtensible Business Reporting Language) has been touted as a new technology that may someday replace HTML (Hypertext Markup Language) as the standard method of statutory filings. This study offers some initial empirical evidence suggesting that retail investors do not use XBRL structured data as much as expected by the SEC (the U.S. Securities and Exchange Commission). The result shows

Abstract We elaborate on behavioral foundations for agent expectations in financial markets and propose a multicomponent model. Components in bounded rational processing and imitative processing that can underlie frequently cited “herding” in financial markets are proposed in the agent-based model. We define a transition function for the dominance of a component in the distance between market price

Abstract We develop a tractable model in which asset prices are driven by the epidemic spread of certain investment ideas. Once an idea “goes viral,” equilibrium prices exhibit a pattern of boom and bust. In turn, we identify a timeline of symptoms, which indicate whether a boom is in its early or later stages. Moreover, we find that prices start to decline while the number of infected agents, who

Abstract This paper reexamines the issue of behavioral heterogeneity in the stock market. In contrast to previously documented contemporaneous results, we test the issue by identifying and testing four new determinants of the proportion of fundamentalists and chartists in the stock market. Our empirical results are consistent with the following notions. First, the proportion of fundamentalists increases

Abstract This study tests the presence of herding behavior in commodity markets (energy, industrial metals, precious metals, grains food, and livestock) from a constant and time-varying perspective. Additionally, we investigate whether oil prices and major financial indicators drive herding in these markets. Using daily data over the period 2003–2017, the constant model based on the cross-sectional

Abstract Relying on over 300 million news sentiment scores from a global news source covering a battery of different news topics and their sentiment, we construct a novel measure called top news sentiment based on rolling correlations with equity returns. We find an effect of top news sentiment on stock returns with robust timeframes. These findings add to the sentiment literature with the first dynamically

Abstract Herding is a feature of investor behavior in financial markets, particularly in market stress. We apply an approach based on the cross-sectional dispersion of individual stocks' betas, which allows us to extract herding patterns, using two dynamic methodologies to measure the herding phenomenon over time with a state-space model for the Cryptocurrency Market. The results reveal that herding

Abstract We analyze the ability of a newspaper-based economic sentiment index of the United States to predict housing market movements using daily data from 2nd August, 2007 to 19th June, 2020. For this purpose, we use a nonparametric causality-in-quantiles test, which allows us to test for predictability over the entire conditional distribution of not only housing returns, but also volatility, by

Abstract We investigate the presence of feedback trading in 66 currencies for the 2001–2018 period and find that feedback traders are active in many of them, giving rise mostly to positive feedback trading, when present. This suggests that feedback traders assume a stabilizing role, buying when currencies depreciate and selling when they appreciate, with depreciations found to boost positive feedback

Abstract Business valuations of the same company made by different valuators frequently diverge, resulting in lengthy and costly disputes. This paper takes a novel approach in explaining inconsistencies in business valuations by adopting a psychological perspective and offering a first investigation into the role of cognitive biases in valuations. In two experimental studies (N = 331) we show that

Abstract The general purpose of stock price prediction is to help stock analysts design a strategy to increase stock returns. We present the conceptual framework of an emotion-based stock prediction system (ESPS) focused on considering the multidimensional emotions of individual investors. To implement and evaluate the proposed ESPS, emotion indicators (EIs) are generated using emotion term frequency–inverse

Abstract We hypothesize that upward social comparison of asset holdings among traders exacerbates leveraged asset bubbles because traders shift their frame of reference from profit maximization toward quantity maximization, increasing price momentum. In addition, asset prices should inflate even more in markets with wealth inequality because the relative reference shift becomes stronger. We test this

Abstract While finance studies suggest that forecast-confidence motivates trading, the experimental findings regarding the confidence-trading links are inconclusive and statistically weak. Attempting to bridge the gap, we modify the standard interval forecasting task to measure forecast-confidence more directly. The adapted task is utilized to test the confidence-trading correlations at the attitudinal

Abstract This article investigates the suitability of 13 investor sentiment proxies as causal explanations for monthly stock returns of the European S&P 350 constituents over 45 years. We analyzed a sample of 362 companies covering 16 European countries. Analyses incorporate multiple categories of investor sentiment arising from market or survey data, as well as technical analysis, risk measures, company

Abstract This study investigates the differential effect of anger and fear on investors information search behavior. Based on theories from psychology, I predict that angry investors will seek out less additional information and exert a lower depth of thought than fearful investors after a negative earnings surprise. Additionally, I predict that these differences will be moderated in investors that

Abstract The authors analyze how the citizens’ attitude toward the future, obtained using big data, affects the relationship between the nation’s financial development and economic growth. The relationship between financial development and economic growth has been ambiguous, as the literature supports both positive and negative effects of financial development on economic growth. We find that the individual’s

Abstract The underlying physiological mechanisms of biases are not well understood. As such, we examine the impact of testosterone and cortisol levels on several commonplace investment biases using realistic trading simulations. Cortisol, the biological marker of stress, is positively related to the disposition effect and portfolio turnover, which is consistent with the relation between judgment errors

Abstract Using a direct measure of investor attention generated from the Securities and Exchange Commission’s EDGAR (Electronic Data Gathering, Analysis, and Retrieval) log files, the authors revisit the stock return predictability of the divergence of opinions in the presence of varying degree of investor attention and information acquisition. They document a positive relationship between the divergence

Abstract The authors investigate the impact of social media on S&P index constituents for U.S., European, and emerging markets with the international investor perspective using firm-specific Twitter sentiment and activity. The findings indicate that Twitter activity and sentiment are associated with trading volume and returns, and predicts subsequent-day trading volume. The authors find that firm-specific