Studies from Manipal Academy of Higher Education Reveal New Findings on Risk Management (Evaluation and Prediction of Stock Market Crash Risk in Mexico Using Log-Periodic Power-Law Modeling): Insurance – Risk Management

Insurance Daily News

2026 FEB 11 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Data detailed on risk management have been presented. According to news originating from Manipal, India, by NewsRx correspondents, research stated, “This study applies the Log-Periodic Power-Law (LPPL) framework to three major equity markets-Mexico (IPC), Brazil (IBOVESPA), and the United States (NYSE Composite)-using daily closes from 8 November 1991-30 January 2025 for IPC and NYSE, and 3 May 1993-30 January 2025 for IBOVESPA.”

Our news journalists obtained a quote from the research from Manipal Academy of Higher Education: “Multi-window calibrations (L e 180, 240, 300, 360, 420) are estimated in raw and log space to evaluate bubble signatures and the stability of the critical time t c. Across all indices, log-space fits consistently outperform raw fits in terms of RMSE and R 2 , and longer windows reduce parameter variability, yielding coherent clusters of t c. Under full-sample conditions, the LPPL structure points to March-April 2025 for NYSE, mid-October 2025 for IBOVESPA, and October-December 2025 for IPC, while shorter windows pull t c forward. A rolling early-warning ensemble translates these estimates into lead-based risk bands, with numerical reporting used when median leads fall just outside the 60-trading-day decision horizon. The early-2025 weakening in the U.S. market is consistent with the NYSE cluster, whereas Brazil and Mexico remain within their projected windows as of September 2025.”

According to the news reporters, the research concluded: “The analysis highlights the strengths of LPPL-behavioral interpretability and hazard-based framing-while noting limitations such as window sensitivity and parameter sloppiness, reinforcing the need for conservative communication and the use of longer-window weighting in practical applications.”

For more information on this research see: Evaluation and Prediction of Stock Market Crash Risk in Mexico Using Log-Periodic Power-Law Modeling. Risks, 2026,14(1):3. (Risks - http://www.mdpi.com/journal/risks). The publisher for Risks is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/risks14010003.

Our news editors report that additional information may be obtained by contacting Suryansh Sunil, Department of Aeronautical and Automobile Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India. Additional authors for this research include Amit Kumar Goyal, Rajesh Mahadeva, Varun Sarda.