Before revision:  While it is a long standing consensus that leverage effects exist, empirical evidence paradoxically show that most individual stocks either do not exhibit this correlation or are very weak. This, at least partially, is due to an assumption that the correlationis linear, i. e., the effect of large shocks and small fluctuations changes linearly. We relax this standard assumption of linear correlation to a nonlinear generalization in order to capture the complex nature of this effect using a newly developed Bayesian sequential computation method that is fast, efficient, and on-line  . Examining 615 stocks that comprise the S  P500 and Nikkei 225, we find nearly all of the stocks to exhibit leverage effects, of which many would have been lost under the standard linear assumption.
After revision:  While it is a long standing consensus that leverage effects exist, empirical evidence paradoxically show that most individual stocks either do not exhibit this correlation . We examine this paradox by questioning the validity of the assumption of linearity in the correlation. Nonlinear generalizations of the leverage effect are proposed within the stochastic volatility framework in order to capture the complex nature of this effect using a newly developed Bayesian sequential computation method that is fast, efficient, and on-line . Examining 615 stocks that comprise the S P500 and Nikkei 225, we find nearly all of the stocks to exhibit leverage effects, of which many would have been lost under the standard linear assumption.