Monetary Policy Shocks and Multi-scale Positive and Negative Bubbles in an Emerging Country: The Case of India

Oguzhan Cepni, Rangan Gupta, Jacobus Nel*, Joshua Nielsen

*Corresponding author for this work

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Abstract

We employ the Multi-Scale Log-Periodic Power Law Singularity Confidence Indicator (MS-LPPLS-CI) approach to identify positive and negative bubbles in the short-, medium, and long-term for the Indian stock market, using weekly data from November 2003 to December 2020. We use a nonparametric causality-in-quantiles approach to analyze the predictive impact of monetary policy shocks on bubble indicators. We find, in general, strong evidence of predictability across the entire conditional distribution for the two monetary policy shock factors, with stronger impacts for negative bubbles. Our findings have critical implications for the Reserve Bank of India, academics, and investors.
Original languageEnglish
Article number35
Journal Financial Innovation
Volume11
Number of pages25
ISSN2199-4730
DOIs
Publication statusPublished - Jan 2025

Keywords

  • Multi-scale positive and negative bubbles
  • Monetary policy shocks
  • Nonparametric causality-in-quantiles test
  • India

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