The review in Part I suggests that traditional models and approaches, though appealing and successful in some limited applications, do not appear to describe bubble and crash events adequately or satisfyingly. This part begins with an overview of the central role played by the equity risk premium, which provides the main, but perhaps not the only, reference series that can be used in developing an elasticity-of-variance concept. This concept makes possible the empirical identification and strength measurement of bubbles and crashes and is applicable to forecasting.

Although the discussion here is also wide-ranging, the main departure from neoclassical Walrasian economic theories of equilibrium is that, especially in bubbles and crashes, holding quantity desired, much more than price received or offered, is what drives the process. The works of Bénassy and Malinvaud provide the theoretical underpinning for this approach.

It is then shown that bubbles and crashes can be empirically described when the elasticity-of-variance measurements within any period follow an exponential path and form “micro-bubbles” and “micro-crashes.” The more such micro events occur within a sample period, the stronger is the entire event. As the sampling period can be as brief as minutes or as long as months or years, the theory is time-scale independent and consistent with the idea that market prices are fractal.

This theory is then linked to aspects of behavioral finance, and it is shown that the standard equity-risk premium contains a behavioral risk premium component that can be estimated from transactions-volume changes.