Liquidity Spillover Effects of Equity Offerings Over Dual-Class Shares

Abstract

We study the spillover effect from equity offerings over dual-class shares. Whereas, evidence has been found that a seasoned equity offering improves stock liquidity, the effect over the liquidity of different type shares of the same firm has not been explored. We use equity offerings of five Latin American countries: Brazil, Chile, Colombia, Mexico and Peru, during 1995 to 2012, because dual-class shares are widely used in the regions. In spite of the expected information asymmetry reduction, using panel data models we found a stock liquidity reduction of dual-class shares upon the offering; consistent with trading migration effects, according with the theory of inventory costs.JEL Classification: G12, G14, G15.

Measuring Return and Volatility Spillovers among Sectoral Stocks in Nigeria

“…Of the papers surveyed in this study, just one study have examined volatility transmissions in the Nigerian stock market (see, Kpughur er al,, 2017) however, it adopts aggregate data and examines transmissions between the naira exchange rate and the stock market using approaches different from this study. There are also studies for other regions, worthy of mention is China (see, e.g., Wang and Zhang, 2011;Sharma, 2017;Jebran et al, 2017), BRICS (see, e.g., Ramaprasad and Biljana, 2007;Boubaker and Raza, 2017;Nareshet al, 2018), U.S (see, e.g., Arouri et al, 2011;Ghouse and Khan, 2017;Kinnunen, 2017;Oh, 2017;Bekiros et al, 2016), Europe (see, e.g., Arouri et al, 2011;Chang et al, 2013;Sharma, 2017;Blau, 2017), South America (see, e.g., Vasco and Agudelo, 2014;Gamba-Santamaria et al, 2016)among others. Furthermore, we notice that there are few or no studies on returns and volatility transmission at the sectoral level in Sub Saharan African regions, this is probably due to data inadequacies or constraints.…”

“…In the literature, differing methods have been used to examine returns and volatility transmissions in stock markets. Some of the prominent techniques include; General Autoregressive Conditional Heteroscedasticity (GARCH) models (see, e.g., Ramaprasad and Biljana, 2007;Arouri et al, 2011;Chang et al, 2013;Jebran, et al, 2017;Kpughur et al, 2017;Ghouse and Khan, 2017;Apergis and Gupta, 2017;Boubaker and Raza, 2017), Vector Autoregression (see, e.g., Andrikopoulos et al, 2014;Baoko and Alagidede, 2017;Sharma, 2017;Kinnunen, 2017), Regression analysis (see, e.g., Wang and Zhang, 2011;Vasco and Agudelo, 2014;Fauzi and Wahyudi, 2016;Blau, 2017) to mention a few.…”