2011/12/31 by Ola Løvsletten, Martin Rypdal · 17 citations
Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · #Applied mathematics #Artificial intelligence #Complex Systems and Time Series Analysis #Computer science #Financial Risk and Volatility Modeling #Fractal #Inference #Mathematical analysis #Mathematics #Maximum likelihood #Multifractal system #Random walk #Statistics #Theoretical and Computational Physics #Truncation (statistics) #physics.data-an #q-fin.ST
paper · pdf · doi:10.1103/physreve.85.046705
published in Physical Review E 85(4), 046705 (American Physical Society) · 8 pages, 3 figures, 2 tables
arxiv created 2012/02/22 · openalex publication_date 2012/04/27 · arxiv updated 2015/06/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We present an approximated maximum likelihood method for the multifractal random walk processes of [E. Bacry et al., Phys. Rev. E 64, 026103 (2001)]. The likelihood is computed using a Laplace approximation and a truncation in the dependency structure for the latent volatility. The procedure is implemented as a package in the r computer language. Its performance is tested on synthetic data and compared to an inference approach based on the generalized method of moments. The method is applied to estimate parameters for various financial stock indices.