Public news arrival and the idiosyncratic volatility puzzle

Shi, Yanlin; Liu, Wai M.; Ho, Kin Yip

doi:10.1016/j.jempfin.2016.03.001

Cited by 47 publications

(18 citation statements)

References 33 publications

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“…Second, as suggested by the statistical results, the presence of negative news prior to an IPO increases the probability to withdraw by as much as 14%, which is a remarkably large effect. This result is not surprising considering the importance of market sentiment and the effect of negative signals (Shi et al, 2016). Negative news stories are easily accessible through the public press.…”

Section: Insert Figures 4 and 5 About Herementioning

confidence: 76%

“…Since IPOs tend to come in waves (Nguyen Thanh, 2019), we examine a hotness dummy, as well as a trading volume dummy (Chemmanur and He, 2011). Recent research on market sentiment theorises that negative public news affects stock returns (Shi et al, 2016) 5 . Finally, we rely upon the end of the month market estimate of volatility (VIX) to further approximate investor sentiment (Busaba et al, 2015).…”

Section: Insert Table 3 About Herementioning

confidence: 99%

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The determinants of IPO withdrawal – Evidence from Europe

Helbing

Lucey

Vigne

2019

Journal of Corporate Finance

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Why do companies not follow through with an IPO after filing for one? This question is investigated by examining common stock IPOs for the largest countries in Europe. We cover 80% of the Western European IPO market over the 2001-2015 period. We establish that the IPO phenomenon of withdrawal is a common feature of equity markets and identify key characteristics that influence the probability of withdrawal. Findings indicate that venture capital or private equity involvement, the presence of negative news, CEO duality, or the intent to retire debt increase the probability of IPO withdrawal. On the other hand, higher levels of corporate governance or trading volume decrease the probability of IPO withdrawal. We argue that imminent agency conflicts and the lack of appropriate control mechanisms can force a company to withdraw from the IPO.

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Section: Insert Figures 4 and 5 About Herementioning

confidence: 76%

Section: Insert Table 3 About Herementioning

confidence: 99%

The determinants of IPO withdrawal – Evidence from Europe

Helbing

Lucey

Vigne

2019

Journal of Corporate Finance

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“…Specifically, Raven Pack's data is not limited to keywords or simple mentions alone but instead assesses the roles focal entities (e.g., CEOs; CEOs' firms) play and assigns a relevance score from 0 to 100 based upon the degree to which a focal entity is central to the news article or press release. Hafez () finds that about 80% of all news articles are low in relevance and filtering for relevance can improve the accuracy of measurement upwards of 300% while Shi, Liu, and Ho () find that failing to restrict for relevance can affect results such that previously identified relationships become insignificant after removing less relevant sources. As such, we first filter to include events with relevance scores equal to 100 to ensure the focal entity is central to the news article or press release (Dai, Parwada, & Zhang, ; Dang, Moshirian, & Zhang, ).…”

Section: Methodsmentioning

confidence: 99%

Second‐order effects of CEO characteristics: How rivals' perceptions of CEOs as submissive and provocative precipitate competitive attacks

Hill

Recendes

Ridge

2018

Strategic Management Journal

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Research Summary: Integrating victimization into competitive dynamics and upper echelons theorizing, we develop and test theory articulating how rivals' perceptions of a CEO precipitate attacks on the CEO's firm. Rather than treating CEOs' characteristics solely as perpetrating action (a first-order effect, like research integrating upper echelons into competitive dynamics), we argue firms with CEOs possessing characteristics perceived as more submissive or more provocative are subject to more competitive actions directed toward their firms (a secondorder effect, like victimization research). Empirical analyses of a sample of Fortune 500 CEOs supports our theorizing while interviews of executives corroborate our premise as well. Our framework offers a more complete and socialized understanding of CEOs' roles in competitive dynamics, providing both theoretical and practical insights as well as future research avenues. Managerial Summary: We articulate how CEOs possessing certain psychological, behavioral, and social characteristics may unknowingly precipitate competitive attacks on their firms. Our explanation integrates insights from victimology which explain how individuals are subject to more attacks if they possess characteristics others perceive as more submissive or more provocative. While prior research articulates that CEOs' characteristics affect decisions such as attacking rivals, integrating theories of victimization into this line of inquiry paints a more socialized view of why firms may be subject to competitive attacks as well. The logic and evidence we provide advances theoretical explanations of firms' competitive behaviors and executives' roles therein. At the same time, providing knowledge about how CEO characteristics precipitate

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“…For statistical scoring, the same approach can be taken as with any machine learning classification procedure – at this point there is nothing special about the fact that the vector values are representations of some textual attribute. Common techniques include neural networks (Thomson Reuters, ), Bayes classifier (Shi et al ., ), support vector machines (SVM), decision trees, random forests and k‐nearest neighbours (kNN). Reviews of these and other classification methods, and their relative performance in the context of text mining, are provided by Sebastiani () and Ravi and Ravi ().…”

Section: Textual Analysis Techniquesmentioning

confidence: 99%

“…For formation periods exceeding one day, these measures may either be computed daily before being averaged over the entire formation period (Uhl, ; Sinha, ), or pooled together at once (Cahan et al ., ). It is also common for each document to be weighted by some measure of relative importance such as story relevance (Ho et al ., ; Shi et al ., ), or, in the case of aggregations over sector and market indices, by firm market capitalisation (Smales, ).…”

Section: Econometric Techniquesmentioning

confidence: 99%

News media analytics in finance: a survey

Marty

Vanstone

Hahn³

2019

Accounting & Finance

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We survey the works applying text analytics to the study of news media in financial markets beyond intraday horizons, and expand into the fundamental economic theory and concepts relevant to the field. We compare and contrast the news sources, textual analysis methods and empirical modelling approaches adopted within the literature. We distil and categorise the key empirical insights, and summarise the bibliographic history of the literature so far. While this rapidly growing field has yielded many exciting discoveries, there are a number of promising avenues for future research which will only benefit from continued advances in computational technology.

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Public news arrival and the idiosyncratic volatility puzzle

Cited by 47 publications

References 33 publications

The determinants of IPO withdrawal – Evidence from Europe

The determinants of IPO withdrawal – Evidence from Europe

Second‐order effects of CEO characteristics: How rivals' perceptions of CEOs as submissive and provocative precipitate competitive attacks

News media analytics in finance: a survey

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