The asset price bubbles in emerging financial markets: a new statistical approach

TL;DR

This paper introduces a new statistical method for detecting and quantifying asset price bubbles in emerging markets, especially where traditional fundamental-based methods are infeasible due to lack of data.

Contribution

The paper proposes a simple, effective statistical approach that does not rely on fundamental values, suitable for immature markets, and can analyze various influences on bubbles.

Findings

Method successfully applied to real stock markets

Can quantify bubble influence factors like herding and fluctuations

Applicable to markets lacking fundamental data

Abstract

The bubble is a controversial and important issue. Many methods which based on the rational expectation have been proposed to detect the bubble. However, for some developing countries, epically China, the asset markets are so young that for many companies, there are no dividends and fundamental value, making it difficult (if not impossible) to measure the bubbles by existing methods. Therefore, we proposed a simple but effective statistical method and three statistics (that is, C, U, V) to capture and quantify asset price bubbles, especially in immature emerging markets. To present a clear example of the application of this method to real world problems, we also applied our method to re-examine empirically the asset price bubble in some stock markets. Our main contributions to current literature are as follows: firstly, this method does not rely on fundamental value, the discount rates and dividends, therefore is applicable to the immature markets without the sufficient data of such kinds, secondly, this new method allows us to examine different influences (herding behavior, abnormal fluctuation and composite influence) of bubble. Our new statistical approach is, to the best of our knowledge, the only robust way in existing literature to to quantify the asset price bubble especially in emerging markets.