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doi:10.1111/jofi.2001.56.issue-1

Cited by 19 publications

(15 citation statements)

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“…First, we follow Campbell et al (2001) and measure risk by the variance of stock excess returns relative to the risk-free rate during the first month of the offer. Thereafter, the issuing firm risk is decomposed into a systematic risk component associated with extrinsic factors and an idiosyncratic risk associated with firm intrinsic factors.…”

Section: Ipo Risk Measuresmentioning

confidence: 99%

“…Campbell et al (2001) use the variance of shocks in firm returns as a proxy for firm idiosyncratic risk. Hence, it is interesting to separate the variance of shocks in the individual issuing firm returns from its total variance given the asymmetric information that characterizes the IPO market.…”

Section: Introductionmentioning

confidence: 99%

“…where TOTRISK i;τ ¼ VARðR i; j À R f ; j Þ corresponds to the first-month total risk of IPO i (τ = 1) computed throughout the first 21 trading days ( j), SV Campbell et al (2001) and Bali et al (2005) use the CAPM to assess systematic and idiosyncratic risks. 6 Spiegel and Wang (2005) use the SD of the residuals from the three-factor model of Fama and French (1993) to measure idiosyncratic risk.…”

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confidence: 99%

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Firm-specific risk and IPO market cycles

Beaulieu

Bouden

2015

Applied Economics

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Chaire RBC en innovations financières. Centre interuniversitaire sur le risque, les politiques économiques et l'emploi (CIRPÉE). Département de finance, assurance et immobilier, Faculté des sciences de l'administration, Université Laval, Québec G1V 0A6, CanadaThis article characterizes the role of risk in the initial public offering (IPO) cycle. While most of the previous literature uses the volatility of IPO initial returns to measure risk, we focus on different risk measures, namely firmlevel systematic and idiosyncratic volatilities and the market-wide implied volatility index (VIX), to assess their role in the IPO cycle. Our results shed new light on (1) which risk measure is important in the determination of IPO cycles, (2) the temporal pattern of each risk component across issuing firms and (3) the relationship between market-wide uncertainty and IPO risk. Our findings reveal a lead-lag relationship between IPO waves, VIX and the IPO systematic risk measure. We also highlight the fact that marketlevel uncertainty predicts IPO activity and the level of idiosyncratic risk of the next-period-issuing firms. Issuing firms' systematic risk can only be predicted by the systematic risk of firms now proceeding to their offering. The main implication resulting from our study is that one can better anticipate 'hot-issue' markets, as well as the specific risk components of future new issues. This will help improve upon the regulatory environment, IPO investment decisions and IPO timing given market receptivity.

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Section: Ipo Risk Measuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Firm-specific risk and IPO market cycles

Beaulieu

Bouden

2015

Applied Economics

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“…However, many researchers' performed studies identifying the stock market unsystematic risk premium. For example, Aaker and Jacobson (1987), Cox and Griepentrog (1988), Barber (1994), and Campbell, Lettau, Malkiel, and Xu (2001), Goyal and Santa-Clara (2003) find that unsystematic risk premium is positively related to return, whereas Cheung and Wong (1992), Bali and Cakici (2008), and Bollen, Skotnicki, and Veeraraghavan (2009) report no significant relationships between the idiosyncratic risk and returns in the US, Australia, and Hong Kong markets, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Given the importance to water investment, the issue of idiosyncratic risk and returns has not received appropriate attention in the past literature. The water investment literature indicates that few studies have been done thus far (see Antoniou, Barr, & Priestley, 2000;Buckland & Fraser, 2000, 2001Buckland & Williams, 2013;Geman & Kanyinda, 2007;Gilroy, Schreckenberg, & Seiler, 2013;Jin et al, 2015a,b;Morana & Sawkins, 2000;Roca & Tularam, 2012;Roca et al, 2015). However, other studies on the systematic risk and return of investment in the water industry have been done in great depth (Wong et al, 2007).…”

Section: Literature Reviewmentioning

confidence: 99%

Water exchange traded funds: A study on idiosyncratic risk using Markov switching analysis

Tularam

Reza

2016

Cogent Economics & Finance

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Abstract:We investigate the relationship between idiosyncratic risk and return among four water exchange traded funds-PowerShares Water Resources Portfolio, Power Shares Global Water, First Trust ISE Water Index Fund, and Guggenheim S&P Global Water Index ETF using the Markov switching model for the period 2007-2015. The generated transition probabilities in this paper show that there is a high and low probability of switching between Regimes 1 and 3, respectively. Moreover, we find that the idiosyncratic risk for most of the exchange traded funds move from low volatility (Regime 2) to very low volatility (Regime 1 and 3). Our study also identify that the beta coefficients are positive and entire values are less than 1. Thus, it seems that water investment has a lower systematic risk and a positive effect on the water exchange traded index funds returns during different regimes.

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Pairs trading: does volatility timing matter?

Huck¹

2015

Applied Economics

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online novembre 2014 compté en 2014International audiencePairs trading is a dollar-neutral trading strategy. Using the components of two major stock indices, the S&P 500 and the Nikkei 225, this article deals with the performance of a pairs trading system based on various pairs selection methods (distance, stationarity, cointegration) over a 10-year period. On both markets, using a classical framework, cointegration appears superior and effective. On the U.S. market and also in Japan to a lower extent, pairs trading strategies exhibited an impressive performance during the 2008 financial crisis. Bearish periods are associated with a high level of the VIX index: the ‘investor fear gauge’. Using a modified trading system, this article examines the link between pairs trading performance and volatility/VIX timing. It is shown that for the best selection technique (cointegration), timing volatility has no economic value in a pairs trading context

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Cited by 19 publications

References 0 publications

Firm-specific risk and IPO market cycles

Firm-specific risk and IPO market cycles

Water exchange traded funds: A study on idiosyncratic risk using Markov switching analysis

Pairs trading: does volatility timing matter?

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