The volatility effect in emerging markets

Blitz, David; Pang, Juan; Vliet, Pim van

doi:10.1016/j.ememar.2013.02.004

Cited by 136 publications

(24 citation statements)

References 22 publications

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“…For our region-or country-neutral analyses, we occasionally find a significantly positive relation between risk and return as one would expect from standard textbook finance. Blitz, Pang, and Van Vliet (2012) suggest that low-risk strategies also earn higher risk-adjusted returns in emerging equity markets. However, they observe that in the first half of their sample (1989-1999) the low-risk effect in emerging markets is weaker than in the second half of their sample (2000-2010).…”

Section: Low-riskmentioning

confidence: 99%

The cross-section of stock returns in frontier emerging markets

Groot¹,

Pang²,

Swinkels

2012

Journal of Empirical Finance

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113

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We are the first to investigate the cross-section of stock returns in the new emerging equity markets, the so-called frontier emerging markets. Our unique survivorship-bias free data set consists of more than 1,400 stocks over the period 1997 to 2008 and covers 24 of the most liquid frontier emerging markets. The major benefit of using individual stock characteristics is that it allows us to investigate whether return factors that have been documented in developed countries also exist in these markets. We document the presence of economically and statistically significant value and momentum effects, and a local size effect. Our results indicate that the value and momentum effects still exist when incorporating conservative assumptions of transaction costs. Additionally, we show that value, momentum, and local size returns in frontier markets cannot be explained by global risk factors.

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Section: Low-riskmentioning

confidence: 99%

The cross-section of stock returns in frontier emerging markets

Groot¹,

Pang²,

Swinkels

2012

Journal of Empirical Finance

Self Cite

113

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“…Some researchers supported the validity of the model (Bajpai & Sharma, 2015;Bjuggren & Eklund, 2015;Lee, Cheng, & Chong, 2016;Novak, 2015) while others concluded that the model is invalid in estimating the expected rate of return on the financial asset (Alqisie & Alqurran, 2016;Alrgaibat, 2015;Chaudhary, 2017;Wu et al, 2017). In Jordan, however, many researchers concluded that the single-factor model is invalid (Blitz, Pang, & Van Vliet, 2013;Alqisie & Alqurran, 2016;Alrgaibat, 2015).…”

Section: Capital Asset Pricing Modelmentioning

confidence: 99%

Testing a Multi-factor Capital Asset Pricing Model in the Jordanian Stock Market

Elshqirat¹,

Sharifzadeh²

2018

IBR

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A valid and accurate capital asset pricing model (CAPM) may help investors and mutual funds managers in determining expected returns which may lead to increase their profits and community resources. The problem is that the traditional CAPM does not accurately predict the expected rate of return. A more accurate model is needed to help investors in determining the intrinsic price of the financial asset they want to sell or buy. The purpose of this study was to examine the validity of the single-factor CAPM and then develop and test a multifactor CAPM in the Jordanian stock market. The study was informed by the modern portfolio theory and specifically by the single-factor CAPM developed by Sharpe, Lintner, and Mossin. The research questions for the study examined the factors that may explain the variation in the expected rate of return on stocks in the Jordanian stock market and the relationship between the expected rate of return and factors of market return, company size, financial leverage, and operating leverage. A causal-comparative quantitative research design was employed to achieve the purpose of the study by testing the listed companies on the Amman stock exchange (ASE) for the period from 2000 to 2015. Data were collected from the ASE database and analyzed using the multiple regression model and t test. The results revealed that market return, company size, and financial leverage are not predictors of the expected rate of return while operating leverage is a predictor.

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“…Their empirical results support both models when performed against an unspecified alternative, but support the CAPM when an MLPM alternative is specified. Blitz, Pang, and van Vliet (2013) study the significant effects of volatility in emerging markets. De Groot, Pang, and Swinkels (2012) demonstrate the significant presence of value, momentum, and size effects in frontier emerging markets over the period 1997 to 2008; the authors argue that transaction costs or risk do not adequately explain these three market factors.…”

Section: Literature Reviewmentioning

confidence: 99%

Value-at-Risk and Expected Stock Returns: Evidence from Pakistan

Iqbal

Azher

2014

LJE

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This study investigates whether exposure to downside risk, as measured by value-at-risk (VaR), explains expected returns in an emerging market, i.e., Pakistan. We find that portfolios with a higher VaR are associated with higher average returns. In order to explore the empirical performance of VaR at the portfolio level, we use a time series approach based on 25 size and book-to-market portfolios. Based on monthly portfolio data for October 1992 to June 2008, the results show that VaR has greater explanatory power than the market, size, and book-to-market factors.

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The volatility effect in emerging markets

Cited by 136 publications

References 22 publications

The cross-section of stock returns in frontier emerging markets

The cross-section of stock returns in frontier emerging markets

Testing a Multi-factor Capital Asset Pricing Model in the Jordanian Stock Market

Value-at-Risk and Expected Stock Returns: Evidence from Pakistan

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