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 …

We use the multi-scale Log-Periodic Power Law Singularity (LPPLS) confidence indicator
approach to detect both positive and negative bubbles at short-, medium-and long-run for …

Using monthly data for the G7 countries from 1973 to 2020, we study whether stock market
bubbles help to forecast out-of-sample the realized volatility of oil price returns. We use the …

This paper studies the relationship between financial stability and sustainable development
from the fiscal and monetary policy perspective in 33 developing countries and 7 developed …

Financial markets are frequently exposed to a variety of crises at the national, regional, and
global levels, with potentially heterogeneous effects on market performance. To make sound …

This paper uses the bootstrap rolling-window Granger causality method to investigate the
relationship between US monetary policy (UMP) and crude oil price (COP). The method …

This paper examines the predictability of bubbles across global stock markets and whether
or not synchronicity in bubble formation can be predicted via metrics of market risk that are …

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 …

This paper examines the effects of Islamic economic and social systems within a democratic
environment on the causal relationships among uncertainty, informal economy, corruption …

We study whether booms and busts in the stock market of the United States (US) drives its
volatility. Given this, first, we employ the Multi-Scale Log-Periodic Power Law Singularity …