Tootfinder

Confronting General Relativity with Principal Component Analysis: Simulations and Results from GWTC-3 Events
Parthapratim Mahapatra, Sayantani Datta, Ish Gupta, Poulami Dutta Roy, Muhammed Saleem, Purnima Narayan, Soumen Roy, Jan Steinhoff, Deirdre Shoemaker, Alan J. Weinstein, Anuradha Gupta, B. S. Sathyaprakash, K. G. Arun
https://arxiv.…

Confronting General Relativity with Principal Component Analysis: Simulations and Results from GWTC-3 Events
We present a comprehensive assessment of multiparameter tests of general relativity (GR) in the inspiral regime of compact binary coalescences using Principal Component Analysis (PCA). Our analysis is based on an extensive set of simulated gravitational wave signals, including both general relativistic and non-GR sources, injected into zero-noise data colored by the noise power spectral densities of the LIGO and Virgo detectors at their designed sensitivities. We evaluate the performance of PCA…

Behavioral Probability Weighting and Portfolio Optimization under Semi-Heavy Tails
Ayush Jha, Abootaleb Shirvani, Ali M. Jaffri, Svetlozar T. Rachev, Frank J. Fabozzi
https://arxiv.org/abs/2507.04208

Behavioral Probability Weighting and Portfolio Optimization under Semi-Heavy Tails
This paper develops a unified framework that integrates behavioral distortions into rational portfolio optimization by extracting implied probability weighting functions (PWFs) from optimal portfolios modeled under Gaussian and Normal-Inverse-Gaussian (NIG) return distributions. Using DJIA constituents, we construct mean-CVaR99 frontiers, alongwith Sharpe- and CVaR-maximizing portfolios, and estimate PWFs that capture nonlinear beliefs consistent with fear and greed. We show that increasing tai…