Behavioral finance argues that some properties of asset prices are most reasonably considered as deviations from fundamental value and they are caused by the presence of traders who are not fully rational hence called noise traders. Noise trader approach assumes that sentiment traders exert greater influence during highsentiment periods than during low-sentiment periods, and sentiment traders misestimate the variance of returns weakening the mean-variance relation. This study’s main objective is to provide a framework to model conditional volatility regarding the changes in the investor sentiment by measuring the effect of noise trader demand shocks on the volatility of stock market indexes of the various countries. GARCH, TARCH, and EGARCH models are used to test whether earning shocks have more influence on the conditional volatility in high sentiment periods weakening the mean-variance relation. This paper takes an international approach using weekly and daily returns of Nasdaq, Dow, S&P500, Nikkei225, HangSeng, FTSE100, CAC40, DAX, and ISE indexes. Weekly and daily trading volume changes of these indexes are used as a proxy for investor sentiment and significant evidence is found that there is asymmetric volatility in these market indexes and earning shocks have more influence on conditional volatility when the sentiment is high.