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...

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 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...

Books reviewed: The European Central Bank: The New European Leviathan, by D. Howarth and P. Loedel The European System of Central Banks: An Autonomous Actor? The Quest for an Institutional Balance in EMU, by B. Dutzler The Law of the European Central Bank, by C. Zilioli and M. Selmayr Europe in...

Books reviewed in this article: J. Monar and W. Wessels (eds.), The European Union after the Treaty of Amsterdam D. Nicol, EC Membership and the Judicialization of British Politics G. de Burca and J. H. H. Weiler (eds.), The European Court of Justice R. Bellamy and A. Warleigh (eds.),...

In dose-response studies, the dose range is often restricted due to ethics concerns over drug toxicity and/or efficacy, particularly when human subjects are involved. We present locally optimal designs for the estimation of several percentiles simultaneously on restricted as well as unrestricted...

We consider a class of optimality criteria and show that each crite- rion has its unique and equivalent dual within the class. This property can be used to find a variety of optimal designs, including a class of compound optimal designs and their relationships. As an example, we show that one...