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A Search Model of Financial Bubbles (Working Paper)
This paper develops a search-and-matching model to provide a micro-foundation for the "ride-the-tide" behavior of speculators during financial bubbles. While existing literature often struggles to simultaneously explain the two prominent stylized facts of bubbles—explosive asset prices and abnormally high trade volumes—this model endogenously generates both within a strictly rational framework. The explosive price path and complex volume dynamics are jointly driven by the compositional shift of heterogeneous investors and the rational expectation of an approaching collapse risk.
A key contribution of this model is its empirical tractability. The framework translates theoretical mechanisms into a functional Simulated Maximum Likelihood Estimator (SMLE). By matching the dynamic paths of observed market data, the estimation can structurally recover unobservable fundamental values and endogenously forecast potential turning points of a bubble.
Figure 1: Simulated Market Price Index
This figure illustrates the endogenous asset price dynamics generated by the model. The aggregate price index exhibits an explosive, convex path prior to the collapse risk, driven by the shift in investor composition and the rational expectation of an impending crash. After the critical period, the price index experiences a sharp decline driven by the forced disposal process.
Figure 2: Rolling Structural Estimation on the Dot-com Bubble
This figure demonstrates the model's empirical capability as an early-warning system. By running the Simulated Maximum Likelihood Estimator (SMLE) on restricted historical sub-samples (green shaded areas) of the NASDAQ index, the model endogenously projects the impending turning point (the blue dashed line) strictly prior to the actual historical crash.
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