出版社：The International Institute for Science, Technology and Education (IISTE)
摘要：Stock price index and market capitalisation were seen to have crashed during the wake of the recent financial meltdown. This research investigates the determinants of stock price volatility in Nigeria. Multiple regression and vector auto regression (VAR) models were utilized to measure the response of stock price to prior price level, capital gain, information, excess demand, and quantity of stock traded using data on daily transaction, covering the period 2005 to 2010. Prior price level and capital gain were found as the overriding factors in stock price determination. However, shocks to stock price account for the largest variation in the future value of stock price. Accordingly, both regulators and companies are urged to stop frequent alteration of prevailing stock price by allowing the market forces to determine the prices while systematically preventing the market against negative external and internal forces.
其他摘要：Stock price index and market capitalisation were seen to have crashed during the wake of the recent financial meltdown. This research investigates the determinants of stock price volatility in Nigeria. Multiple regression and vector auto regression (VAR) models were utilized to measure the response of stock price to prior price level, capital gain, information, excess demand, and quantity of stock traded using data on daily transaction, covering the period 2005 to 2010. Prior price level and capital gain were found as the overriding factors in stock price determination. However, shocks to stock price account for the largest variation in the future value of stock price. Accordingly, both regulators and companies are urged to stop frequent alteration of prevailing stock price by allowing the market forces to determine the prices while systematically preventing the market against negative external and internal forces. Keywords: Stock price index, market capitalization, financial meltdown, Vector autoregressive (VAR) models, stock price determination.
