The return impact of realized and expected idiosyncratic volatility

Peterson, David R.; Smedema, Adam R.

doi:10.1016/j.jbankfin.2011.02.015

Cited by 56 publications

(26 citation statements)

References 39 publications

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“…Regression results in table 6b show that a volatility increase predicts a positive abnormal return. This result is consistent with the literature measuring a negative relation between returns and idiosyncratic volatility, see Ang et al (2006) and Peterson and Smedema (2011). In our sample, high idiosyncratic volatility before completion is associated with a 16 The F variance test between the variance in the period before the announcement (vol1_idio) and the variance in the period between announcement and completion (vol2_idio) rejects the null hypothesis of equality in 21% of the cases instead of 5% (significance level of the test) while the F test between the annualized volatility in the period before the announcement and the variance after completion accepts the null of equality in 92% of the cases (test with a significance level of 5%).…”

Section: <Insert Table 6b Around Here>supporting

confidence: 93%

Is M&A different during a crisis? Evidence from the European banking sector

Beltratti

Paladino

2013

Journal of Banking & Finance

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The financial crisis has affected the landscape of the banking sector around the world. We use a sample of transactions taking place in Europe in 2007-2010 to study the acquirer's stock price market reaction to announcements and completions of acquisitions. We find that there are no significant abnormal returns around the announcement of an acquisition while there are positive abnormal returns at completions. We study the cross-sectional determinants of abnormal returns and find that announcement returns are mainly explained by the acquirer bank characteristics, while completion returns depend on opacity of the target and in large part on the drop in volatility associated with a reduction of uncertainty. 3 1. Introduction.

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Section: <Insert Table 6b Around Here>supporting

confidence: 93%

Is M&A different during a crisis? Evidence from the European banking sector

Beltratti

Paladino

2013

Journal of Banking & Finance

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“…In comparison, the estimated negative impact of the idiosyncratic volatility on the expected return at the monthly, quarterly, and annual frequencies is more challenging to explain. Peterson and Smedema (2011) and Bhootra and Hur (2011), among others, propose possible explanations for a negative idiosyncratic volatility premium. The gist of their explanations is that stocks with relatively high idiosyncratic volatilities may be overvalued by investors, and thus, such stocks could be associated with relatively low subsequent returns (for an example of this argument, see Peterson and Smedema, 2011, pp.…”

Section: Analysis Of Main Resultsmentioning

confidence: 99%

“…In particular, Peterson and Smedema (2011), among others, note that the effect may significantly affect inference regarding the idiosyncratic volatility premium.…”

Section: Analysis Of January Effect and Additional Robustness Checksmentioning

confidence: 99%

“…The models of Levy (1978), Merton (1987), Malkiel and Xu (2006), and Epstein and Schneider (2008) predict a positive premium in the capital market equilibrium. However, research based on Kahneman and Tversky's (1979) prospect theory indicates that the premium can be negative (e.g., see Bhootra and Hur, 2011); an additional explanation for why the premium can be negative has been suggested by Peterson and Smedema (2011).…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, Fu uses an expected conditional idiosyncratic volatility measure by estimating an EGARCH model on a time-series of monthly returns (Fu requires having at least 30 observations in the time-series). Peterson and Smedema (2011) indicate that these alternative measures of idiosyncratic volatility can be associated with different effects on returns. Thus, the divergence in the sign of the idiosyncratic volatility premium (estimated in the second pass of the two-pass approach) may have arisen because some researchers use short-term, high-frequency data, whereas other researchers use long-1 There is also no consensus in the literature on the issues of the forecasting power and the time-series behavior of idiosyncratic volatility.…”

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confidence: 99%

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Impact of Idiosyncratic Volatility on Stock Returns: A Cross-Sectional Study

Khovansky

Zhylyevskyy

2012

SSRN Journal

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This paper proposes a new approach to estimate the idiosyncratic volatility premium. In contrast to the popular two-pass regression method, this approach relies on a novel GMM-type estimation procedure that uses only a single cross-section of return observations to obtain consistent estimates. Also, it enables a comparison of idiosyncratic volatility premia estimated using stock returns with different holding periods. The approach is empirically illustrated by applying it to daily, weekly, monthly, quarterly, and annual US stock return data over the course of 2000-2011. The results suggest that the idiosyncratic volatility premium tends to be positive on daily return data, but negative on monthly, quarterly, and annual data. They also indicate the presence of a January effect. KeywordsIdiosyncratic voltality, idiosyncratic voltality premium, cross-section of stock returns, generalized method of moments Disciplines Econometrics | Growth and Development | Other EconomicsComments NOTICE: this is the author's version of a work that was accepted for publication in Journal of Banking & Finance. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Banking & Finance, [37, 8, (2013) AbstractThis paper proposes a new approach to estimate the idiosyncratic volatility premium. In contrast to the popular two-pass regression method, this approach relies on a novel GMMtype estimation procedure that uses only a single cross-section of return observations to obtain consistent estimates. Also, it enables a comparison of idiosyncratic volatility premia estimated using stock returns with different holding periods. The approach is empirically illustrated by applying it to daily, weekly, monthly, quarterly, and annual U.S. stock return data over the course of 2000-2011. The results suggest that the idiosyncratic volatility premium tends to be positive on daily return data, but negative on monthly, quarterly, and annual data. They also indicate the presence of a January effect.JEL classification: G12, C21

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Global idiosyncratic risk moments

Baghdadabad

Mallik

2017

Empir Econ

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The return impact of realized and expected idiosyncratic volatility

Cited by 56 publications

References 39 publications

Is M&A different during a crisis? Evidence from the European banking sector

Is M&A different during a crisis? Evidence from the European banking sector

Impact of Idiosyncratic Volatility on Stock Returns: A Cross-Sectional Study

Global idiosyncratic risk moments

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