Abstract

An alternative approach to examine stock market volatility based on the percentages of extreme days, weeks, and months out of a year period is applied to the G-7 group of seven countries and three other western European countries. Compared with the traditional standard deviation method, we find a similar volatility pattern for both measures. 1n addition, the extreme measure has three benefits: dividing volatility into positive and negative parts; classifying volatility as different levels and allowing researchers evidently to recognize the length of the volatile period for each level during a specified period; and having flexibility to self define extreme measures depending on various research requirements. When we apply the extreme-day measure to examine investor behaviors in Canada, the U.S. and the U.K., we find that the extreme-day measure more efficiently explains Canadian investor behavior than the standard deviation does.