An Application of the “Recursive Flexible Window” Methodology to Test for Financial Bubbles in a Major Stock Market

IF 0.4 Q4 ECONOMICS
Swarna D. Dutt, Dipak Ghosh
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引用次数: 0

Abstract

Identifying and dating financial bubbles in real time is in the forefront of current empirical research. Their accuracy provides real time useful “warning alerts” to central bankers and fiscal regulators. The complexity of their nonlinear structure and the inherent sudden break mechanisms makes the econometric testing challenging. The new recursive flexible window methodology provided by Phillips, Shi, and Yu (2015) gives consistent results and delivers significant power gains when multiple bubbles occur. It successfully identifies well-known historical episodes of exuberance and collapse. In this paper we look at the Indian stock market indices, the SENSEX, and the NIFTY 50, to see if there is any evidence of a bubble there. We use monthly data for each series, with the Sensex data spanning April 1979 to October 2018 and NIFTY 50 data spanning July 1990 to October 2018. The existence of bubbles in this index will give us some indication of where bubbles are more likely to occur, and therefore provide evidence of potential economic (financial) crises.
“递归弹性窗口”方法在主要股市金融泡沫检验中的应用
实时识别和确定金融泡沫的时间是当前实证研究的前沿。它们的准确性为央行行长和财政监管机构提供了实时有用的“警告警报”。其非线性结构的复杂性和固有的突发性断裂机制给计量检验带来了挑战。Phillips、Shi和Yu(2015)提供的新的递归柔性窗口方法给出了一致的结果,并在多个气泡发生时提供了显着的功率增益。它成功地识别出了众所周知的繁荣与崩溃的历史时期。在本文中,我们研究了印度股市指数,SENSEX指数和NIFTY 50指数,看看是否有任何泡沫的证据。我们使用每个系列的月度数据,Sensex数据涵盖1979年4月至2018年10月,NIFTY 50数据涵盖1990年7月至2018年10月。该指数中泡沫的存在将为我们提供一些泡沫更有可能发生的迹象,从而为潜在的经济(金融)危机提供证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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