2020
DOI: 10.1016/j.iref.2020.05.008
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The idiosyncratic momentum anomaly

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Cited by 52 publications
(37 citation statements)
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References 44 publications
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“…Using the model selection criterion suggested by Akaike, the AIC which can be seen in detail in Gujarati and Porter (2011) or Wooldridge (2012), the market model to estimate the idiosyncratic risk was selected. With the alpha and betas parameters greater than zero, the volatility models estimated in this work assume their general form performed by the expressions described below: the ARCH (q) model represented by the expression (4); the GARCH (p, q) model represented by expression (5); the IGARCH (p, q) model represented by expression (6); the EGARCH (p, q, r) model represented by the expression (7); and TGARCH (p, q, r) model represented by the expression (8).…”
Section: Methodological Approachmentioning
confidence: 99%
See 1 more Smart Citation
“…Using the model selection criterion suggested by Akaike, the AIC which can be seen in detail in Gujarati and Porter (2011) or Wooldridge (2012), the market model to estimate the idiosyncratic risk was selected. With the alpha and betas parameters greater than zero, the volatility models estimated in this work assume their general form performed by the expressions described below: the ARCH (q) model represented by the expression (4); the GARCH (p, q) model represented by expression (5); the IGARCH (p, q) model represented by expression (6); the EGARCH (p, q, r) model represented by the expression (7); and TGARCH (p, q, r) model represented by the expression (8).…”
Section: Methodological Approachmentioning
confidence: 99%
“…In general, market volatility increases in the periods leading up to these crises and during crisis periods, as observed by Kalra (2008) in the recent period of the world economy with the subprime crisis. Among the most recent studies that attempt to estimate idiosyncratic risk, it can be mention Blitz et al (2020) which deals with this risk as an anomaly can be mentioned, Chang et al (2018) with data from the Japanese economy, and Shi and Zhou (2019) that verify the idiosyncratic risk of the Chinese stock market. This work aims to estimate the idiosyncratic risk or unique risk of the Latin American economies and the emerging economies using heteroscedastic conditional models of the ARCH family models to verify the impact of the Covid-19 pandemic on the risk associated with productive projects developed in the Latin American countries, namely, Argentine, Brazil, Chile, Colombia, Mexico and Peru, and the other emerging countries as well as on the risk associated with investments and financing.…”
Section: Introductionmentioning
confidence: 99%
“…Zaremba (2018) studies the momentum effect in 40 cross sectional anomalies for 78 countries and finds momentum effect to be present in more than half of such anomalies. Blitz et al (2018) document the existence of the idiosyncratic momentum effect in non-U.S. countries. Similarly, Linnainmaa and Roberts (2018) support that profitability anomaly subsumes most of the earnings-related anomalies.…”
Section: Literature Reviewmentioning
confidence: 97%
“…Over time, different strategies based on momentum effect have been suggested by researchers (Alhenawi, 2015; Barroso & Santa-Clara, 2015; Blitz et al, 2018; Chang et al, 2018; Conrad & Yavuz, 2017; Daniel & Moskowitz, 2016; Moskowitz et al, 2012; Novy-Marx, 2012; Novy-Marx & Velikov, 2015; Pukthuanthong et al, 2019; Vu, 2012). Zaremba (2018) examines momentum effect among different anomalies in 78 countries and observes that half of the anomalies among sample countries have momentum effect.…”
Section: Literature Reviewmentioning
confidence: 99%