Saeed Fathi – Recent Articles

Decomposition of the dividend forecast model: firm characteristics or market discrimination? Evidence from the Korean market
Injoong Kim
Afro-Asian J. of Finance and Accounting, Vol. 10, No. 2 (2020) pp. 278 - 294
Historically, KOSPI firms have shown consistently higher chances of dividend payment compared to KOSDAQ firms. The counterfactual decomposition technique popularised by Oaxaca and Blinder is adapted to explain the dividend differentials between the two markets. Our results suggest that there exists market discrimination that cannot be explained by the traditional dividend forecast model of Fama and French (2001). After controlling for the group differences in firm characteristics such as size and profitability, KOSPI firms still have a higher probability of paying dividends, and, especially during the crisis period, they deal with risks better and are less affected by macroeconomic shocks. We observe the level difference after controlling for firm characteristics as well as the difference in the sensitivity of dividends with respect to the dividend predictors between two markets. For the crisis period, the explanatory power of firm characteristics drops, and the market effect plays a dominant role in explaining dividend behaviours.

Analysing the effect of trading characteristics on liquidity measures – a combined approach to liquidity: evidences from Tehran Stock Exchange
Saeed Fathi; Somaye Jalali; Alireza Ajam; Omid Mirmohammad Sadeghi
Afro-Asian J. of Finance and Accounting, Vol. 10, No. 2 (2020) pp. 262 - 277
Liquidity estimation has always been of conspicuous importance to all investors as well as risk and return. The purpose of this study is to examine the impact of trading characteristics (price, trading volume, variability, return volatility, absolute stock return, and Beedles thin trading measure) on liquidity measures (Amihud illiquidity ratio, return reversal measure, stock turnover, zero return, turnover-volatility ratio and proportional bid-ask spread) in Tehran Stock Exchange. We extend previous studies by combining different liquidity measures using TOPSIS technique and by employing a multidimensional variable, namely TOPSIS output. Results reveal both of the liquidity measures are strongly related to trading characteristics including stock turnover and zero return. Also, stock price, trading volume, and Beedles thin trading measures are the most significant factors in estimating liquidity. Different effects of different liquidity measures indicate that liquidity is a multidimensional and complex concept, and each measure reflects only one aspect of liquidity. The results of examining the influence of trading characteristics on the combined (multidimensional) liquidity measure indicate that trading characteristics are the main determinants of liquidity.