Extreme returns and the idiosyncratic volatility puzzle: African evidence

ABSTRACT

We examine the cross-sectional relationship between the expected stock return and both the maximum daily return (MAX) and the idiosyncratic volatility (IVOL) in the five largest emerging African stock markets over the period from 2001 to 2015. First, we find that there is a robust and significantly negative MAX effect in the pooled African stock markets. Second, though we initially document a negative IVOL effect, it disappears after controlling for MAX. Finally, the negative MAX effect is only significant in the small-SIZE, high-illiquidity and high-skewness portfolios. Our results suggest risk-seeking behaviour among African investors similar to that in other parts of the world.

KEYWORDS:

• Maximum daily return
• idiosyncratic volatility
• emerging African stock markets
• financial anomalies

JEL CLASSIFICATION:

• F39
• G11
• G12
• G14

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

¹ However, Egginton and Hur (2018) report that the MAX and IVOL effects co-exist when they restrict their sample to stocks to those that are overpriced and have a price greater than $5.

² Tolikas (2011) reports that except for the South Africa stock market, other African stock markets are underdeveloped; however, these stock markets have consistently increased their market capitalization over the past decade.

³ If a stock has temporary stopped trading for a certain period, DataStream records the value of the return index from the month when the stock stops trading to the month when the stock re-starts the trade. For example, if a stock stops trading from January 2010 to December 2010, then the value of the return index of the stock will remain at the same level during the period.

⁴ To avoid extreme observation and data bias, we omit monthly stock returns above or below 200%.

⁵ We compute the regional factors MKT_d^R, SMB_d^R and HML_d^R as the value-weighted sum of the country factors in Equation (1). The weights were obtained by converting each country’s market capitalization into US dollars.

⁶ There might be a multicollinearity problem between MAX and IVOL in the pooled African stock markets because of a high coefficient of correlation between the two variables. Therefore, following Bali, Cakici, and Whitelaw (2011) and Nartea, Kong, and Wu (2017) we orthogonalize IVOL on MAX whenever both variables are included in the regression.

⁷ We conducted a robustness test on the MAX effect by using 49 stocks with the lowest price in our sample. Results suggest that the MAX effect is significant and negative in univariate, bivariate and multivariate tests. We do not report the results due to space limitation but are available upon request.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China, General Program [71773103] and the Fundamental Research Funds for the Central Universities [20720191007].