Investor trading behaviour and stock price crash risk

Zhou, Liyun; Huang, Jialiang

doi:10.1002/ijfe.1659

Cited by 19 publications

(13 citation statements)

References 54 publications

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“…For example, many studies have focused on firm-level internal factors such as corporate tax avoidance [1], opaque financial reports [2,3], accounting conservatism [4], corporate social responsibility [5], CEO overconfidence [6]), financial constraints [7], stock liquidity [8], corporate financing [9], corporate debt maturity [10], stock ownership [11], equity incentives [12], corporate governance [13], and other cases. However, several other studies on factors such as religion [14,15], social trust [16], media sentiment and mawkishness [17], individualism [18], Sustainability 2021, 13, 3688 2 of 16 political connections [19], trading behavior and sentiment of investors [20,21], and product market competition [22] have tried to investigate a couple of these corporate external factors. This study has a slightly different approach and aims to examine simultaneously the effects of some corporate characteristics as well as the most important macroeconomic external factors on the stock price crash.…”

Section: Introductionmentioning

confidence: 99%

Macroeconomic Factors and Stock Price Crash Risk: Do Managers Withhold Bad News in the Crisis-Ridden Iran Market?

et al. 2021

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The present study aims to investigate the effects of macroeconomic variables on stock price crash risk in the economically uncertain conditions of Iran’s market. This study also seeks to examine whether there is a significant relationship between some firm characteristics and falling stock prices. The sample of the study includes 152 Iranian companies listed on the Tehran Stock Exchange (TSE) between 2014 and 2019. Furthermore, the research model has been estimated using a fixed effect pattern, and the DUVOL (down-to-up volatility) measure is defined as a proxy for stock price crash risk. Consistent with our expectations, the results show that there is a positive association between the inflation and unemployment rates and stock price crash risk, whereas the GDP and exchange rates are correlated negatively with crash risk. In fact, with rising inflation and unemployment, on the one hand, the amount of savings and the purchasing power of the people have decreased, and on the other hand, it has reduced the sales of companies due to the increase in the pricing of manufactured products. In Iran’s economically uncertain situation due to sanctions, managers are trying to overstate financial performance and conceal bad news to have better access to financing; so, when the total amount of bad news accumulated over time reaches a tipping point, it leads to a stock crash. It also appears that when the exchange rate rises, Iranian investors prefer to buy companies’ shares to maintain the purchasing power of their money. Outcomes also confirm that larger firms and those with higher Return on Assets (ROA) are more sensitive to crash risk.

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Section: Introductionmentioning

confidence: 99%

Macroeconomic Factors and Stock Price Crash Risk: Do Managers Withhold Bad News in the Crisis-Ridden Iran Market?

et al. 2021

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“…In addition to the above-mentioned biases, other biases such as hindsight, loss aversion, self-control, endowment, self-attribution, ambiguity aversion, and others are distinguished. Other authors (Tekce et al, 2016;Ye et al, 2020;L. Zhou & Huang, 2019) mention other deviations in investor behavior in financial markets in addition to the biases listed above.…”

Section: Literature Reviewmentioning

confidence: 99%

“…It has been found that individuals are influenced by preconceived notions, stereotypes, various perceptual illusions, information processing errors and emotions when making investment decisions. Clearly, these facts are inconsistent with rational behavior, which is based on classical models, and therefore the science of behavioral finance emphasizes such key features of irrational behavior that characterize the modern investors (Barber & Odean, 2013;Ryu et al, 2017;L. Zhou & Huang, 2019):…”

Section: Literature Reviewmentioning

confidence: 99%

Investigation of the Herding and Contrarian Behaviour of Investors

Maknickienė

Masėnaitė

Stasytytė

et al. 2021

International Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering"

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Purpose – The paper analyses two different paradigms of investor behaviour that exist in the financial mar-ket – the herding and contrarian behaviour. The main objective of the paper is to determine which pattern of investor behaviour better reflects the real changes in the prices of financial instruments in the financial markets. Research methodology – Algorithms of technical analysis, deep learning and classification of sentiments were used for the research; data of positions held by investors were analysed. Data mining was performed using “Tweet Sentiment Visualization” tool. Findings – The performed analysis of investor behaviour has revealed that it is more useful to ground financial decisions on the opinion of the investors contradicting the majority. The analysis of the data on the positions held by investors helped to make sure that the herding behaviour could have a negative impact on investment results, as the opinion of the majority of investors is less in line with changes in the prices of financial instruments in the market. Research limitations – The study was conducted using a limited number of investment instruments. In the future, more investment instruments can be analysed and additional forecasting methods, as well as more records in social networks can be used. Practical implications – Identifying which paradigm of investor behaviour is more beneficial to rely on can offer ap-propriate practical guidance for investors in order to invest more effectively in financial markets. Investors could use investor sentiment data to make practical investment decisions. All the methods used complement each other and can be combined into one investment decision strategy. Originality/Value – The study compared the ratio of open positions not only with real price changes but also with data obtained from the known technical analysis, deep learning and sentiment classification algorithms, which has not been done in previous studies. The applied methods allowed to achieve reliable and original results.

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“…Jia and Yang (2017) use the total market buyer‐initiated volume and the total market seller‐initiated volume data to construct the disagreement of crowded trades index. Zhou and Huang (2019) use the buy‐sell imbalance to represent the investor trading behaviour. If retail investors are net buyers of a given stock over a given time period, then the buy‐sell imbalance is positive.…”

Section: Individual Stock Investor Sentimentmentioning

confidence: 99%

The term structure effects of individual stock investor sentiment on excess returns

2020

Int. J Fin Econ

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In this paper, we construct the individual stock sentiment indexes at daily, weekly and monthly frequencies. We empirically demonstrate the different effects of individual stock sentiment of three frequencies on the excess returns. The results show that the effect of individual stock sentiment on excess returns is a monotonous decreasing function of time term in China's stock market, which presents obvious term structure effect. Moreover, we find that sentiment factor can better explain the variation of excess returns than size factor and book‐to‐market factor do at the same frequency, and thus we should pay more attention to the individual effect of investor sentiment in the short‐term decision‐making. Our results shed new light on the short‐sighted behaviour of irrational investors and the micro‐mechanism of sentiment effect.

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Investor trading behaviour and stock price crash risk

Cited by 19 publications

References 54 publications

Macroeconomic Factors and Stock Price Crash Risk: Do Managers Withhold Bad News in the Crisis-Ridden Iran Market?

Macroeconomic Factors and Stock Price Crash Risk: Do Managers Withhold Bad News in the Crisis-Ridden Iran Market?

Investigation of the Herding and Contrarian Behaviour of Investors

The term structure effects of individual stock investor sentiment on excess returns

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