• Title/Summary/Keyword: 주가급락 위험

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Left-tail Risk and Expected Stock Returns in the Korean Stock Market (국내 주식시장에서 주가급락위험이 기대수익률에 미치는 영향)

  • Cheon, Yong-Ho;Ban, Ju-Il
    • The Journal of the Korea Contents Association
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    • v.21 no.11
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    • pp.320-332
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    • 2021
  • This paper investigates the influence of stock-level left-tail risk, which is defined using Value-at-Risk(VaR) estimates of past one-year daily stock returns, in the expected stock returns in the Korean stock market. Our results are summarized as follows: First, monthly-constructed zero-cost portfolios that buy (shortsell) the highest (lowest) left-tail risk decile in the previous month exhibit an average monthly return (called left-tail risk premium) of -2.29%. Second, Fama-MacBeth cross-sectional regressions suggest that left-tail risk in the previous month shows significant and negative explanatory power over return in this month, after controlling for various firm characteristics such as firm size, B/M, market beta, liquidity, maximum daily return, idiosyncratic volatility, and skewness. Third, the stocks with larger recent month loss have lower returns in the next month. Fourth, the magnitude of left-tail risk premium is negatively related with lagged market-level volatility. These results support the hypothesis from a perspective of behavioral finance that the overpricing of stocks with left-tail risk is attributed to the investors' underreaction to it.

The Effect of Largest Shareholder's Ownership of Chinese Companies and the Stock Price Crash Risk (중국 기업의 최대주주 지분율이 주가급락 위험에 미치는 영향)

  • Yang, Zhi-Wei;Qing, Cheng-Lin
    • Journal of Digital Convergence
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    • v.20 no.1
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    • pp.41-46
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    • 2022
  • Chinese stock market often rises and falls sharply. The impact of the stock price crash risk has become a hot research field to maintain financial stability. This study starts from the perspective of the proportion of largest shareholders holding shares, and studies whether largest shareholders have more incentive to supervise management and reduce self-interest behavior of management. We use the data of Chinese listed companies from 2009 to 2019 as a sample, and study the relationship between largest shareholders and share price crash risk. Empirical research shows that the higher the proportion of largest shareholders of state-owned enterprise, the company's stock price crash risk can be significantly reduced. This study suggests that the higher the share of the largest shareholder, the lower the opportunistic behavior of managers and that information asymmetry between the company and the shareholders can be alleviated.

The Effect of Portal Search Intensity on Stock Price Crash (포털 검색 강도가 주가 급락에 미치는 영향에 관한 연구)

  • Kim, Min-Su;Kwon, Hyuk-Jun
    • The Journal of Society for e-Business Studies
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    • v.22 no.2
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    • pp.153-168
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    • 2017
  • Recent studies focus on the role of investor attention and transparency in stock-related information in explaining stock return and trading volume. Moreover, recent literatures predict that firm opacity will increase the likelihood of future stock price crashes. In this paper, we investigate, using Naver Trend, the relation between portal search intensity and stock price crash. Using various alternative measures of stock price crash risk and search intensity, we demonstrate that stocks with larger volume of portal search are less likely to experience stock price crashes. These results are consistent with our hypothesis that accumulated firm opacity cause future stock price crash. Finally, our results still hold even after we control for the potential effect of endogeneity in the regression specifications.

Family Firms and Stock Price Crash Risk (가족기업과 주가급락위험)

  • Ryu, Hae-Young;Chae, Soo-Joon
    • Asia-Pacific Journal of Business
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    • v.10 no.4
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    • pp.77-86
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    • 2019
  • The purpose of this study is to examine how the characteristics of family firms affect stock price crash risk. Prior studies argued that the opacity of information due to agency problem causes a plunge in stock prices. The governance characteristics of family firms can increase information opacity which leads to crash risk. Therefore, this study verifies whether family firms have a high possibility of stock price crash risk. We use a logistic regression model to test the relationship between family firms and stock price crash risk using listed firms listed on the Korean Stock Exchange during the fiscal years 2011 through 2017. The family firm is defined as the case where the controlling shareholder is the chief executive officer or the registered executive. If the controlling shareholder's share is less than 5%, it is not considered a family business. We found that family firms are more likely to experience a plunge in stock prices. This supports the hypothesis of this study that passive information disclosure behavior and information opacity of family firms increase stock price crash risk.

The Effect of Managerial Overconfidence on Crash Risk (경영자과신이 주가급락위험에 미치는 영향)

  • Ryu, Haeyoung
    • The Journal of Industrial Distribution & Business
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    • v.8 no.5
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    • pp.87-93
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    • 2017
  • Purpose - This paper investigates whether managerial overconfidence is associated with firm-specific crash risk. Overconfidence leads managers to overestimate the returns of their investment projects, and misperceive negative net present value projects as value creating. They even use voluntary disclosures to convey their optimistic beliefs about the firms' long-term prospects to the stock market. Thus, the overconfidence bias can lead to managerial bad news hoarding behavior. When bad news accumulates and crosses some tipping point, it will come out all at once, resulting in a stock price crash. Research design, data and methodology - 7,385 firm-years used for the main analysis are from the KIS Value database between 2006 and 2013. This database covers KOSPI-listed and KOSDAQ-listed firms in Korea. The proxy for overconfidence is based on excess investment in assets. A residual from the regression of total asset growth on sales growth run by industry-year is used as an independent variable. If a firm has at least one crash week during a year, it is referred to as a high crash risk firm. The dependant variable is a dummy variable that equals 1 if a firm is a high crash risk firm, and zero otherwise. After explaining the relationship between managerial overconfidence and crash risk, the total sample was divided into two sub-samples; chaebol firms and non-chaebol firms. The relation between how I overconfidence and crash risk varies with business group affiliation was investigated. Results - The results showed that managerial overconfidence is positively related to crash risk. Specifically, the coefficient of OVERC is significantly positive, supporting the prediction. The results are strong and robust in non-chaebol firms. Conclusions - The results show that firms with overconfident managers are likely to experience stock price crashes. This study is related to past literature that examines the impact of managerial overconfidence on the stock market. This study contributes to the literature by examining whether overconfidence can explain a firm's future crashes.

The Effect of Audit Quality on Crash Risk: Focusing on Distribution & Service Companies (감사품질이 주가급락 위험에 미치는 영향: 유통, 서비스 기업을 중심으로)

  • Chae, Soo-Joon;Hwang, Hee-Joong
    • Journal of Distribution Science
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    • v.15 no.8
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    • pp.47-54
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    • 2017
  • Purpose - According to agency theory, managers have incentives to adjust firm revenues to meet earnings expectations or delay bad news disclosure because of performance-based compensation and their reputation in the market. When the bad news accumulates, stock prices fail to reflect all available information. Thus, market prices of stocks are higher than their intrinsic value. After all, bad news crosses the tipping point, it comes out all at once. That results in stock crashes. Auditors can decrease stock crash risk by reducing agency costs through their informational role. Especially, stock price crash risk is expected to be lower for firms adopting high-quality audits. We focus on distribution and service industry to examine the relation between audit quality and stock price crash risk. Industry specialization and auditor size are used as proxies for auditor quality. Research design, data and methodology - Our sample contains distribution and service industry firms listed in KOSPI and KOSDAQ during a period of 2004-2011. We use a logistic regression to test whether auditor quality influences crash risk. Auditor quality was measured by industry specialist auditor and Big4 / non-Big4 dichotomy. Following the approach in prior researches, we use firm-specific weekly returns to measure crash risk. Firms experiencing at least one stock price crash in a specific week during year are classified as the high risk group. Results - The result of analyzing 429 companies in distribution and service industry is summarized as follows: Above all, it is shown that higher audit quality has a significant negative(-) effect on the crash risk. Crash risk is alleviated for firms audited by industry specialist auditors and Big 4 audit firms. Therefore, our results show that hypotheses are supported. Conclusions - This study is very meaningful as the first study which investigated the effects of high audit quality on stock price crash risk. We provide evidence that high-quality auditors reduce stock price crash risk. Our finding implies that the risk of extreme losses can be reduced through screening of high-quality auditors. Therefore investors and regulators may utilize our findings in their investment and rule making decisions.

The Effect of Control-Ownership Wedge on Stock Price Crash Risk (소유지배 괴리도가 주가급락위험에 미치는 영향)

  • Chae, Soo-Joon;Ryu, Hae-Young
    • The Journal of Industrial Distribution & Business
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    • v.9 no.7
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    • pp.53-59
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    • 2018
  • Purpose - This study examines the effect of control-ownership wedge on stock crash risk. In Korea, controlling shareholders have exclusive control rights compared to their cash flow rights. With increasing disparity, controlling shareholders abuse their power and extract private benefits at the expense of the minority shareholders. Managers who are controlling shareholders of the companies tend not to disclose critical information that would prevent them from pursuing private interests. They accumulate negative information in the firm. When the accumulated bad news crosses a tipping point, it will be suddenly released to the market at once, resulting in an abrupt decline in stock prices. We predict that stock price crash likelihood due to information opaqueness increases as the wedge increases. Research design, data, and methodology - 831 KOSPI-listed firm-year observations are from KisValue database from 2005 to 2011. Control-ownership wedge is measured as the ratio (UCO -UCF)/UCO where UCF(UCO) is the ultimate cash-flow(control) rights of the largest controlling shareholder. Dependent variable CRASH is a dummy variable that equals one if the firm has at least 1 crash week during a year, and zero otherwise. Logistic regression is used to examine the relationship between control-ownership wedge and stock price crash risk. Results - Using a sample of KOSPI-listed firms in KisValue database for the period 2005-2011, we find that stock price crash risk increases as the disparity increases. Specifically, we find that the coefficient of WEDGE is significantly positive, supporting our prediction. The result implies that as controlling shareholders' ownership increases, controlling shareholders tend to withhold bad news. Conclusions - Our results show that agency problems arising from the divergence between control rights and cash flow rights increase the opaqueness of accounting information. Eventually, the accumulated bad news is released all at once, leading to stock price crashes. It could be seen that companies with high control-ownership wedge are likely to experience future stock price crashes. Our study is related to a broader literature that examined the effect of the control-ownership wedge on stock markets. Our findings suggest that the disparity is a meaningful predictor for future stock price crash risk. The results are expected to provide useful implications for firms, regulators, and investors.