This paper investigates dynamic currency hedging benefits, with a further focus on the impact of currency hedging before and during the recent financial crises originated from the subprime and the Euro sovereign bonds. We take the point of view of a Euro-based institutional investor who...

Since 2009, stock markets have resided in a long bull market regime. Passive investment strategies have succeeded during this low-volatility growth period. From 2018 on, however, there was a transition into a more volatile market environment interspersed by corrections increasing in amplitude...

We used the log-periodic power law singularity (LPPLS) methodology to systematically investigate the 2020 stock market crash in the U.S. equities sectors using the Wilshire 5000 Total Market index, the S&P 500 index, the S&P MidCap 400 index, and the Russell 2000 index. During the crash, all...

In this study, we adopted the Log-Periodic Power Law Singularity (LPPLS) model for real-time identification and monitoring of Bitcoin bubbles and crashes using different time scale data and proposed the modified Lagrange regularization method to alleviate the impact of potential LPPLS model...

In this study, we perform a novel analysis of the 2015 financial bubble in the Chinese stock market by calibrating the Log Periodic Power Law Singularity (LPPLS) model to two important Chinese stock indices, SSEC and SZSC, from early 2014 to June 2015. The back tests of the 2015 Chinese stock...

We applied the Log-periodic power law singularity (LPPLS) methodology to analyze the performances of the 10 major global stock market indexes from both developed and emergent stock markets in the 2020 global stock market. The results show that the crashes for the 7 indexes: SP500, DJIA, NASDAQ,...

This article contributes to the quantification of systemic risk within the Moroccan banking system, focusing on listed banks. We utilize indicators derived from Tail Value at Risk and expectiles risk measures, as introduced by El qalli and Said (2013) (El Qalli & Said, 2023), to measure the...

This paper develops a two-step estimation methodology, which allows us to apply catastrophe theory to stock market returns with time-varying volatility and model stock market crashes. Utilizing high frequency data, we estimate the daily realized volatility from the returns in the first step and...