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Analytical stationary distribution of mispricing in the non-linear Chiarella model

Derive the analytical stationary probability density of the mispricing process δ = P − V for the non-linear Chiarella model with cubic fundamentalists' demand f(δ) = κ δ + κ3 δ^3 (as defined in Section 2.2).

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Background

To assess bimodality in mispricing, the authors rely on nonparametric tests and simulation because a closed-form stationary distribution is not available for the non-linear model. This limits direct analytical evaluation of the conditions under which mispricing is bimodal.

Obtaining the stationary density would provide a theoretical foundation for the empirical and numerical findings, enabling explicit characterization of modality and more precise links between parameter values and distributional features.

References

For the analytical stationary probability density is unknown, we probe bimodality via Silverman’s test for multimodality , which tests for a distribution having a minimum of $k+1$ modes, while the null hypothesis is a distribution with at most $k$ modes.

Revisiting the Excess Volatility Puzzle Through the Lens of the Chiarella Model (2505.07820 - Kurth et al., 12 May 2025) in Section 5 (Mispricing Distribution — Bimodality)