Stochastic sensitivity of bull and bear states

Jochen Jungeilges (), Elena Maklakova and Tatyana Perevalova
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Jochen Jungeilges: University of Agder
Elena Maklakova: Ural Federal University
Tatyana Perevalova: Ural Federal University

Journal of Economic Interaction and Coordination, 2022, vol. 17, issue 1, No 9, 165-190

Abstract: Abstract We study the price dynamics generated by a stochastic version of a Day–Huang type asset market model with heterogenous, interacting market participants. To facilitate the analysis, we introduce a methodology that allows us to assess the consequences of changes in uncertainty on the dynamics of an asset price process close to stable equilibria. In particular, we focus on noise-induced transitions between bull and bear states of the market under additive as well as parametric noise. Our results are obtained by combining the stochastic sensitivity function (SSF) approach, a mixture of analytical and numerical techniques, due to Mil’shtein and Ryashko (1995) with concepts and techniques from the study of non-smooth 1D maps. We find that the stochastic sensitivity of the respective bull and bear equilibria in the presence of additive noise is higher than under parametric noise. Thus, recurrent transitions are likely to be observed already for relatively low intensities of additive noise.

Keywords: Stochastic price process; Non-invertible maps; Non-smooth maps; Stochastic sensitivity function; Transitions between stochastic fixed points; Critical intensity (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11403-020-00313-2

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