Abstract
In order to monitor stock market instability in emerging markets, we propose a stock market instability index (SMII) with a corresponding p-value by using a model fitted to a stable period. More precisely, this study considers a random walk model and combines it with a nonparametric model by using Bayesian model averaging. The integrated stock market instability index (iSMII) and its p-value are derived as a posterior expectation of the two models. In this study, an artificial neural network (ANN) is utilized as a nonparametric model.
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