In this paper, we build on Ryan and Wales (1998) and Moschini (1999) and impose curvature conditions locally on the generalized Leontief model, introduced by Diewert (1974). In doing so, we exploit the Hessian matrix of second order derivatives of the reciprocal indirect utility function, unlike Ryan and Wales (1998) and Moschini (1999), who exploit the Slutsky matrix.

This paper studies the relationship between rational herding and cross correlations in security returns. It demonstrates analytically and numerically that herding, as a temporary, fragile convergence of investment behavior, can endogenously induce asset dependency. Furthermore, there exists a self-reinforcing process, in which market extreme events amplify the herd effect, which further exacerbates asset dependency. Considering the Taiwan and U.K. equity markets, we find that the simulated markets in the presence of herding have results closer to the real patterns of asset dependency than a static model with isolated, noninteracting individuals. Our findings cast doubts on the current view that transparent financial regulation is always desirable. Moreover, this paper finds statistical evidence of asymmetric correlation patterns in both the top 50 stocks in the U.K. and Taiwan equity markets. This suggests that portfolio diversification as a means of managing portfolio risk is unlikely to be effective in periods of extreme losses in these markets.