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Institutional Overcrowding Everyday Journal of Behavioral Finance (IF 0.93) Pub Date : 2021-03-05 Numan Ülkü, Olena Onishchenko
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
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Effects of Conventional and Unconventional Monetary Policy Shocks on Housing Prices in the United States: The Role of Sentiment Journal of Behavioral Finance (IF 0.93) Pub Date : 2021-02-26 Petre Caraiani, Rangan Gupta, Chi Keung Marco Lau, Hardik A. Marfatia
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
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Dispersed Analysts’ Forecasts of Firms’ Operational Uncertainties and Stock Returns Journal of Behavioral Finance (IF 0.93) Pub Date : 2021-02-04 Chang Liu, Haiyue Liu, Xi Chen, Yin Zhang, Min Guo
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
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Dispersed Analysts’ Forecasts of Firms’ Operational Uncertainties and Stock Returns Journal of Behavioral Finance (IF 0.93) Pub Date : 2021-02-04 Chang Liu, Haiyue Liu, Xi Chen, Yin Zhang, Min Guo
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
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Strategic Announcement Sequencing: Earnings and M&A Announcements Journal of Behavioral Finance (IF 0.93) Pub Date : 2021-01-20 Huajing Hu, Katarzyna Platt, Chih-Huei (Debby) Su
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
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Selective Attention in Exchange Rate Forecasting Journal of Behavioral Finance (IF 0.93) Pub Date : 2021-01-16 Svatopluk Kapounek, Zuzana Kučerová, Evžen Kočenda
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
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Negativity Bias of Analyst Forecasts Journal of Behavioral Finance (IF 0.93) Pub Date : 2021-01-10 Yuk Ying (Candie) Chang, Wei Hao
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
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Price Clustering, Preferences for Round Prices, and Expected Returns Journal of Behavioral Finance (IF 0.93) Pub Date : 2021-01-07 Benjamin M. Blau, Todd G. Griffith, Ryan J. Whitby
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
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Investors’ Uncertainty and Forecasting Stock Market Volatility Journal of Behavioral Finance (IF 0.93) Pub Date : 2021-01-03 Ruipeng Liu, Rangan Gupta
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
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What Drives Herding Behavior in the Cryptocurrency Market? Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-12-31 Mouna Youssef
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
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Does Perception Matter in Asset Pricing? Modeling Volatility Jumps Using Twitter-Based Sentiment Indices Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-12-31 Anthony Sanford
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
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Bitcoin Sentiment Index, Bitcoin Performance and US Dollar Exchange Rate Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-12-29 Suresh Kumar Oad Rajput, Ishfaque Ahmed Soomro, Najma Ali Soomro
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
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Predicting Housing Market Sentiment: The Role of Financial, Macroeconomic and Real Estate Uncertainties Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-12-26 Hardik A. Marfatia, Christophe André, Rangan Gupta
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
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Retail Investors Use XBRL Structured Data? Evidence from the SEC’s Server Log Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-12-23 Ken H. Guo, Xiaoxiao Yu
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
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Dynamics of Phase Transitions in Expectations for Financial Markets: An Agent-Based, Multicomponent Model Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-11-24 Steven D. Silver, Marko Raseta, Alina Bazarova
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
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Thought Viruses and Asset Prices Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-11-23 Wolfgang Kuhle
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
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Behavioral Heterogeneity in the Stock Market Revisited: What Factors Drive Investors as Fundamentalists or Chartists? Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-11-06 Leon Li, Peter Miu
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
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Do Oil Prices and Financial Indicators Drive the Herding Behavior in Commodity Markets? Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-11-06 Mouna Youssef
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
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When it Pays to Ignore: Focusing on Top News and their Sentiment Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-09-25 Matthias W. Uhl, Milos Novacek
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
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Market Stress and Herding: A New Approach to the Cryptocurrency Market Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-09-24 Gerson de Souza Raimundo Júnior, Rafael Baptista Palazzi, Ricardo de Souza Tavares, Marcelo Cabus Klotzle
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
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High-Frequency Predictability of Housing Market Movements of the United States: The Role of Economic Sentiment Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-09-24 Mehmet Balcilar, Elie Bouri, Rangan Gupta, Clement Kweku Kyei
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
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Feedback Trading in Currency Markets: International Evidence Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-09-21 Mohammad Tayeh, Vasileios Kallinterakis
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
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Are Business Valuators Biased? A Psychological Perspective on the Causes of Valuation Disputes Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-09-21 Marc J. R. Broekema, Niek Strohmaier, Jan A. A. Adriaanse, Jean-Pierre I. van der Rest
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
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Using Deep Learning to Develop a Stock Price Prediction Model Based on Individual Investor Emotions Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-09-18 Jaeheon Chun, Jaejoon Ahn, Youngmin Kim, Sukjun Lee
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
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Social Comparison and Wealth Inequality in a Leveraged Asset Market Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-07-16 Cary Deck, Li Hao, Weineng Xu, Timothy J. Yeager
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
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The Conflicting Links between Forecast-Confidence and Trading Propensity Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-07-15 Doron Sonsino, Yaron Lahav, Amir Levkowitz
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
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A Reappraisal of the Causal Relationship between Sentiment Proxies and Stock Returns Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-07-15 Pedro Manuel Nogueira Reis, Carlos Pinho
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
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Anger, Fear, and Investor’s Information Search Behavior Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-07-01 Michael J. Wynes
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
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Analyzing the Importance of Forward Orientation in Financial Development-Economic Growth Nexus: Evidence from Big Data Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-06-22 Taniya Ghosh, Prashant Mehul Parab, Sohini Sahu
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
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On the Physiology of Investment Biases: The Role of Cortisol and Testosterone Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-06-18 John R. Nofsinger, Fernando M. Patterson, Corey A. Shank
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
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Investor Attention, Divergence of Opinions, and Stock Returns Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-06-18 Zhen Cao, Osman Kilic, Xuewu (Wesley) Wang
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
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Social Media Sentiment in International Stock Returns and Trading Activity Journal of Behavioral Finance (IF 0.93) Pub Date : 2020-06-16 Selin Duz Tan, Oktay Tas
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