Investor sentiment and multi-scale positive and negative stock market bubbles in a panel of G7 countries

Firstly, we use the log-periodic power law singularity multi-scale confidence indicator (LPPLS-CI) approach to detect both positive and negative bubbles in the short-, medium- and long-term stock market indices of the G7 countries. Secondly, we apply heterogeneous coefficients panel data-based regressions to analyse the impact of investor sentiment, proxied by business and consumer confidence indicators, on the indicators of bubbles of the G7. Controlling for the impacts of output growth, inflation, monetary policy, stock market volatility, and growth in trading volumes, we find that investor sentiment increases the positive and reduces the negative LPPLS-CIs, primarily at the medium- and long-term scales for the G7, considered together, with the result being driven by at least five of the seven countries. Our results have important implications for both investors and policymakers, as the collapse (improvement) of investor sentiment can lead to a crash (recovery) in a bull (bear) market.& COPY; 2023 Elsevier B.V. All rights reserved.

Automated summary

In this study, we first use the LPPLS-CI approach to detect bubbles in the stock market indices of the G7 countries in different time frames. Then, we analyze the impact of investor sentiment, proxied by business and consumer confidence indicators, on the bubble indicators using panel data-based regressions. Our findings show that investor sentiment increases positive bubbles and reduces negative bubbles, primarily in the medium- and long-term scales, and this effect is observed in at least five out of the seven countries. These results have important implications for investors and policymakers, as they suggest that changes in investor sentiment can drive market crashes or recoveries.