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US 2019/0102920 A1Published application
Jointly estimating the hurst exponent and volatility of time series
AssigneeUl Lusenn
InventorsJosselin Gilbert Garnier, Knut Solna
Life of this patent
Estimating the term…
Abstract
A method comprising: in a computer system having at least a processor and a memory, the memory having at least an operating system, using wavelets to form a scale spectrum; and computing estimated Hurst and volatility parameters derived from the scale spectrum.
Claims6
A method comprising:
- in a computer system having at least a processor and a memory, the memory having at least an operating system, using wavelets to form a scale spectrum;
- and
- computing estimated Hurst and volatility parameters derived from the scale spectrum.
A method comprising:
- in a computer systems having at least a processor and a memory, the memory having at least an operating system, computing Haar wavelet coefficients, the Haar wavelet coefficients representing local averages of a data vector, the computing done at all possible averaging lengths and all possible center points for an averaging window;
- for each location of the window, computing an energy (mean square value) of the Haar coefficients whose center points are within the window, computing the energy (mean square value) of the Haar coefficients determined separately for each group of Haar coefficients, based on a certain averaging length, the energy as a function of the Haar coefficient averaging length referred to as a scale spectrum;
- and
- computing Hurst coefficient and volatility as a function of the moving window's center point derived from a slope and an intercept of the scale spectrum in a log-log plot.
1 more element
An architecture comprising:
- a network of interconnected computers;
- and
- a link from the network to a computing device, the computing device having at least a processor and a memory, the memory having at least an operating system and a process to determine for jointly estimating a Hurst exponent and a volatility of time series, the process comprising:
- computing Haar wavelet coefficients, the Haar wavelet coefficients representing local averages of a data vector, the computing done at all possible averaging lengths and all possible center points for an averaging window;
- for each location of the window, computing an energy (mean square value) of the Haar coefficients whose center points are within the window, computing the energy (mean square value) of the Haar coefficients determined separately for each group of Haar coefficients, based on a certain averaging length, the energy as a function of the Haar coefficient averaging length referred to as a scale spectrum;
- and
- computing Hurst coefficient and volatility as a function of the moving window's center point derived from a slope and an intercept of the scale spectrum in a log-log plot.
4 more elements
Dependencies are inferred from the claim text.