Discretization of Continuous Time Discrete Scale Invariant Processes: Estimation and Spectra
arXiv:1601.04405 · doi:10.1007/s10955-016-1541-9
Abstract
Imposing some flexible sampling scheme we provide some discretization of continuous time discrete scale invariant (DSI) processes which is a subsidiary discrete time DSI process. Then by introducing some simple random measure we provide a second continuous time DSI process which provides a proper approximation of the first one. This enables us to provide a bilateral relation between covariance functions of the subsidiary process and the new continuous time processes. The time varying spectral representation of such continuous time DSI process is characterized, and its spectrum is estimated. Also, a new method for estimation time dependent Hurst parameter of such processes is provided which gives a more accurate estimation. The performance of this estimation method is studied via simulation. Finally this method is applied to the real data of SP500 and Dow Jones indices for some special periods.
15 pages
References in corpus (4)
- Discrete scale invariance and complex dimensions
- Renormalization Group Analysis of the 2000-2002 anti-bubble in the US S&P 500 index: Explanation of the hierarchy of 5 crashes and Prediction
- Self-Similar Log-Periodic Structures in Western Stock Markets from 2000
- Spectral Analysis of Multi-dimensional Self-similar Markov Processes