This paper provides an analysis of crude oil, diesel, and gasoline prices for the period from
November 1, 2019 to December 31, 2020. We apply Log Periodic Power-Law Singularity …

Stock price crash risk is of particular interest in developing countries as it poses a significant
threat to investors and can have detrimental effects on the stability of emerging markets. This …

This article provides a systematic review of the theoretical and empirical academic literature
on the development and extension of the log‐periodic power law singularity (LPPLS) model …

Abstract Starting on February 20, 2020, the global stock markets began to suffer the worst
decline since the Great Recession in 2008, and the COVID-19 has been widely blamed on …

Correlations are ubiquitous in nature and their principled study is of paramount importance
in scientific development. The seminal contributions from John Bell offer a framework for …

In this study, the Log-Periodic Power Law Singularity (LPPLS) model is adopted for real-time
identification and monitoring of Bitcoin bubbles and crashes using different time scale data …

A fuzzy inference system consists of a machine learning concept that combines accuracy
and interpretability. They are divided into two main groups: Mamdani and Takagi–Sugeno …

This paper investigates the presence of financial bubbles in the environmentally friendly
investments captured by the ESG markets. By using the log-periodic power law singularity …

We present a heuristic argument for the propensity of Topological Data Analysis (TDA) to
detect early warning signals of critical transitions in financial time series. Our argument is …

The study of critical phenomena that originated in the natural sciences has been extended to
the financial economics' field, giving researchers new approaches to risk management …